id	sid	tid	token	lemma	pos
fcis-6362	1	1	frontiers	frontier	NOUN
fcis-6362	1	2	in	in	ADP
fcis-6362	1	3	computing	computing	NOUN
fcis-6362	1	4	and	and	CCONJ
fcis-6362	1	5	intelligent	intelligent	ADJ
fcis-6362	1	6	systems	system	NOUN
fcis-6362	1	7	issn	issn	VERB
fcis-6362	1	8	:	:	PUNCT
fcis-6362	1	9	2832	2832	NUM
fcis-6362	1	10	-	-	SYM
fcis-6362	1	11	6024	6024	NUM
fcis-6362	1	12	|	|	NOUN
fcis-6362	1	13	vol	vol	NOUN
fcis-6362	1	14	.	.	PROPN
fcis-6362	2	1	3	3	NUM
fcis-6362	2	2	,	,	PUNCT
fcis-6362	2	3	no	no	INTJ
fcis-6362	2	4	.	.	NOUN
fcis-6362	2	5	1	1	NUM
fcis-6362	2	6	,	,	PUNCT
fcis-6362	2	7	2023	2023	NUM
fcis-6362	2	8	167	167	NUM
fcis-6362	2	9	using	use	VERB
fcis-6362	2	10	bidirectional	bidirectional	ADJ
fcis-6362	2	11	prompt	prompt	ADJ
fcis-6362	2	12	learning	learning	NOUN
fcis-6362	2	13	in	in	ADP
fcis-6362	2	14	nlp	nlp	ADJ
fcis-6362	2	15	few	few	ADJ
fcis-6362	2	16	shot	shot	NOUN
fcis-6362	2	17	tasks	task	NOUN
fcis-6362	2	18	li	li	PROPN
fcis-6362	2	19	ding	ding	PROPN
fcis-6362	2	20	,	,	PUNCT
fcis-6362	2	21	shiren	shiren	VERB
fcis-6362	2	22	ye	ye	PROPN
fcis-6362	2	23	*	*	PUNCT
fcis-6362	2	24	school	school	NOUN
fcis-6362	2	25	of	of	ADP
fcis-6362	2	26	computer	computer	NOUN
fcis-6362	2	27	science	science	NOUN
fcis-6362	2	28	and	and	CCONJ
fcis-6362	2	29	artificial	artificial	ADJ
fcis-6362	2	30	intelligence	intelligence	NOUN
fcis-6362	2	31	changzhou	changzhou	PROPN
fcis-6362	2	32	university	university	PROPN
fcis-6362	2	33	,	,	PUNCT
fcis-6362	2	34	changzhou	changzhou	PROPN
fcis-6362	2	35	213164	213164	NUM
fcis-6362	2	36	,	,	PUNCT
fcis-6362	2	37	china	china	PROPN
fcis-6362	2	38	*	*	PUNCT
fcis-6362	2	39	corresponding	correspond	VERB
fcis-6362	2	40	author	author	NOUN
fcis-6362	2	41	:	:	PUNCT
fcis-6362	2	42	shiren	shiren	ADJ
fcis-6362	2	43	ye	ye	PROPN
fcis-6362	2	44	(	(	PUNCT
fcis-6362	2	45	email	email	NOUN
fcis-6362	2	46	:	:	PUNCT
fcis-6362	2	47	yes@cczu.edu.cn	yes@cczu.edu.cn	NOUN
fcis-6362	2	48	)	)	PUNCT
fcis-6362	2	49	abstract	abstract	NOUN
fcis-6362	2	50	:	:	PUNCT
fcis-6362	2	51	few	few	ADJ
fcis-6362	2	52	-	-	PUNCT
fcis-6362	2	53	shot	shot	NOUN
fcis-6362	2	54	learning	learning	NOUN
fcis-6362	2	55	,	,	PUNCT
fcis-6362	2	56	a	a	DET
fcis-6362	2	57	subfield	subfield	NOUN
fcis-6362	2	58	of	of	ADP
fcis-6362	2	59	machine	machine	NOUN
fcis-6362	2	60	learning	learning	NOUN
fcis-6362	2	61	,	,	PUNCT
fcis-6362	2	62	aims	aim	VERB
fcis-6362	2	63	to	to	PART
fcis-6362	2	64	solve	solve	VERB
fcis-6362	2	65	the	the	DET
fcis-6362	2	66	problem	problem	NOUN
fcis-6362	2	67	of	of	ADP
fcis-6362	2	68	learning	learn	VERB
fcis-6362	2	69	new	new	ADJ
fcis-6362	2	70	tasks	task	NOUN
fcis-6362	2	71	with	with	ADP
fcis-6362	2	72	only	only	ADV
fcis-6362	2	73	a	a	DET
fcis-6362	2	74	small	small	ADJ
fcis-6362	2	75	amount	amount	NOUN
fcis-6362	2	76	of	of	ADP
fcis-6362	2	77	annotated	annotate	VERB
fcis-6362	2	78	data	datum	NOUN
fcis-6362	2	79	.	.	PUNCT
fcis-6362	3	1	compared	compare	VERB
fcis-6362	3	2	to	to	ADP
fcis-6362	3	3	traditional	traditional	ADJ
fcis-6362	3	4	supervised	supervised	ADJ
fcis-6362	3	5	learning	learning	NOUN
fcis-6362	3	6	,	,	PUNCT
fcis-6362	3	7	few	few	ADJ
fcis-6362	3	8	-	-	PUNCT
fcis-6362	3	9	shot	shot	NOUN
fcis-6362	3	10	learning	learning	NOUN
fcis-6362	3	11	is	be	AUX
fcis-6362	3	12	more	more	ADV
fcis-6362	3	13	challenging	challenging	ADJ
fcis-6362	3	14	because	because	SCONJ
fcis-6362	3	15	there	there	PRON
fcis-6362	3	16	are	be	VERB
fcis-6362	3	17	very	very	ADV
fcis-6362	3	18	few	few	ADJ
fcis-6362	3	19	training	training	NOUN
fcis-6362	3	20	samples	sample	NOUN
fcis-6362	3	21	available	available	ADJ
fcis-6362	3	22	during	during	ADP
fcis-6362	3	23	the	the	DET
fcis-6362	3	24	training	training	NOUN
fcis-6362	3	25	process	process	NOUN
fcis-6362	3	26	,	,	PUNCT
fcis-6362	3	27	which	which	PRON
fcis-6362	3	28	means	mean	VERB
fcis-6362	3	29	that	that	SCONJ
fcis-6362	3	30	the	the	DET
fcis-6362	3	31	model	model	NOUN
fcis-6362	3	32	must	must	AUX
fcis-6362	3	33	learn	learn	VERB
fcis-6362	3	34	quickly	quickly	ADV
fcis-6362	3	35	and	and	CCONJ
fcis-6362	3	36	generalize	generalize	VERB
fcis-6362	3	37	to	to	ADP
fcis-6362	3	38	new	new	ADJ
fcis-6362	3	39	samples	sample	NOUN
fcis-6362	3	40	.	.	PUNCT
fcis-6362	4	1	prompt	prompt	ADJ
fcis-6362	4	2	learning	learning	NOUN
fcis-6362	4	3	is	be	AUX
fcis-6362	4	4	a	a	DET
fcis-6362	4	5	recently	recently	ADV
fcis-6362	4	6	emerged	emerge	VERB
fcis-6362	4	7	training	training	NOUN
fcis-6362	4	8	paradigm	paradigm	NOUN
fcis-6362	4	9	in	in	ADP
fcis-6362	4	10	natural	natural	ADJ
fcis-6362	4	11	language	language	NOUN
fcis-6362	4	12	processing	processing	NOUN
fcis-6362	4	13	,	,	PUNCT
fcis-6362	4	14	which	which	PRON
fcis-6362	4	15	can	can	AUX
fcis-6362	4	16	quickly	quickly	ADV
fcis-6362	4	17	leverage	leverage	VERB
fcis-6362	4	18	the	the	DET
fcis-6362	4	19	language	language	NOUN
fcis-6362	4	20	capabilities	capability	NOUN
fcis-6362	4	21	of	of	ADP
fcis-6362	4	22	large	large	ADJ
fcis-6362	4	23	pre	pre	ADJ
fcis-6362	4	24	-	-	ADJ
fcis-6362	4	25	trained	train	VERB
fcis-6362	4	26	language	language	NOUN
fcis-6362	4	27	models	model	NOUN
fcis-6362	4	28	to	to	PART
fcis-6362	4	29	achieve	achieve	VERB
fcis-6362	4	30	fast	fast	ADJ
fcis-6362	4	31	start	start	NOUN
fcis-6362	4	32	-	-	PUNCT
fcis-6362	4	33	up	up	NOUN
fcis-6362	4	34	.	.	PUNCT
fcis-6362	5	1	based	base	VERB
fcis-6362	5	2	on	on	ADP
fcis-6362	5	3	the	the	DET
fcis-6362	5	4	prompt	prompt	ADJ
fcis-6362	5	5	learning	learning	NOUN
fcis-6362	5	6	paradigm	paradigm	NOUN
fcis-6362	5	7	,	,	PUNCT
fcis-6362	5	8	this	this	DET
fcis-6362	5	9	paper	paper	NOUN
fcis-6362	5	10	proposes	propose	VERB
fcis-6362	5	11	to	to	PART
fcis-6362	5	12	use	use	VERB
fcis-6362	5	13	its	its	PRON
fcis-6362	5	14	conjugate	conjugate	ADJ
fcis-6362	5	15	tasks	task	NOUN
fcis-6362	5	16	to	to	PART
fcis-6362	5	17	further	far	ADV
fcis-6362	5	18	enhance	enhance	VERB
fcis-6362	5	19	the	the	DET
fcis-6362	5	20	model	model	NOUN
fcis-6362	5	21	's	's	PART
fcis-6362	5	22	ability	ability	NOUN
fcis-6362	5	23	in	in	ADP
fcis-6362	5	24	few	few	ADJ
fcis-6362	5	25	-	-	PUNCT
fcis-6362	5	26	shot	shot	NOUN
fcis-6362	5	27	learning	learning	NOUN
fcis-6362	5	28	.	.	PUNCT
fcis-6362	6	1	the	the	DET
fcis-6362	6	2	experimental	experimental	ADJ
fcis-6362	6	3	results	result	NOUN
fcis-6362	6	4	show	show	VERB
fcis-6362	6	5	that	that	SCONJ
fcis-6362	6	6	the	the	DET
fcis-6362	6	7	proposed	propose	VERB
fcis-6362	6	8	method	method	NOUN
fcis-6362	6	9	can	can	AUX
fcis-6362	6	10	effectively	effectively	ADV
fcis-6362	6	11	improve	improve	VERB
fcis-6362	6	12	the	the	DET
fcis-6362	6	13	performance	performance	NOUN
fcis-6362	6	14	of	of	ADP
fcis-6362	6	15	the	the	DET
fcis-6362	6	16	model	model	NOUN
fcis-6362	6	17	on	on	ADP
fcis-6362	6	18	multiple	multiple	ADJ
fcis-6362	6	19	datasets	dataset	NOUN
fcis-6362	6	20	and	and	CCONJ
fcis-6362	6	21	can	can	AUX
fcis-6362	6	22	be	be	AUX
fcis-6362	6	23	combined	combine	VERB
fcis-6362	6	24	quickly	quickly	ADV
fcis-6362	6	25	with	with	ADP
fcis-6362	6	26	other	other	ADJ
fcis-6362	6	27	methods	method	NOUN
fcis-6362	6	28	for	for	ADP
fcis-6362	6	29	joint	joint	ADJ
fcis-6362	6	30	optimization	optimization	NOUN
fcis-6362	6	31	.	.	PUNCT
fcis-6362	7	1	keywords	keyword	NOUN
fcis-6362	7	2	:	:	PUNCT
fcis-6362	7	3	few	few	ADJ
fcis-6362	7	4	-	-	PUNCT
fcis-6362	7	5	shot	shot	NOUN
fcis-6362	7	6	;	;	PUNCT
fcis-6362	7	7	natural	natural	ADJ
fcis-6362	7	8	language	language	NOUN
fcis-6362	7	9	processing	processing	NOUN
fcis-6362	7	10	;	;	PUNCT
fcis-6362	7	11	prompt	prompt	ADJ
fcis-6362	7	12	learning	learning	NOUN
fcis-6362	7	13	.	.	PUNCT
fcis-6362	8	1	1	1	X
fcis-6362	8	2	.	.	X
fcis-6362	8	3	introduction	introduction	NOUN
fcis-6362	8	4	natural	natural	ADJ
fcis-6362	8	5	language	language	NOUN
fcis-6362	8	6	processing	processing	NOUN
fcis-6362	8	7	(	(	PUNCT
fcis-6362	8	8	nlp	nlp	NOUN
fcis-6362	8	9	)	)	PUNCT
fcis-6362	8	10	is	be	AUX
fcis-6362	8	11	an	an	DET
fcis-6362	8	12	important	important	ADJ
fcis-6362	8	13	research	research	NOUN
fcis-6362	8	14	direction	direction	NOUN
fcis-6362	8	15	in	in	ADP
fcis-6362	8	16	the	the	DET
fcis-6362	8	17	fields	field	NOUN
fcis-6362	8	18	of	of	ADP
fcis-6362	8	19	computer	computer	NOUN
fcis-6362	8	20	science	science	NOUN
fcis-6362	8	21	and	and	CCONJ
fcis-6362	8	22	artificial	artificial	ADJ
fcis-6362	8	23	intelligence	intelligence	NOUN
fcis-6362	8	24	.	.	PUNCT
fcis-6362	9	1	its	its	PRON
fcis-6362	9	2	aim	aim	NOUN
fcis-6362	9	3	is	be	AUX
fcis-6362	9	4	to	to	PART
fcis-6362	9	5	enable	enable	VERB
fcis-6362	9	6	computers	computer	NOUN
fcis-6362	9	7	to	to	PART
fcis-6362	9	8	understand	understand	VERB
fcis-6362	9	9	,	,	PUNCT
fcis-6362	9	10	process	process	NOUN
fcis-6362	9	11	,	,	PUNCT
fcis-6362	9	12	and	and	CCONJ
fcis-6362	9	13	generate	generate	VERB
fcis-6362	9	14	natural	natural	ADJ
fcis-6362	9	15	language	language	NOUN
fcis-6362	9	16	in	in	ADP
fcis-6362	9	17	order	order	NOUN
fcis-6362	9	18	to	to	PART
fcis-6362	9	19	better	well	ADV
fcis-6362	9	20	interact	interact	VERB
fcis-6362	9	21	with	with	ADP
fcis-6362	9	22	humans	human	NOUN
fcis-6362	9	23	.	.	PUNCT
fcis-6362	10	1	the	the	DET
fcis-6362	10	2	development	development	NOUN
fcis-6362	10	3	history	history	NOUN
fcis-6362	10	4	of	of	ADP
fcis-6362	10	5	natural	natural	ADJ
fcis-6362	10	6	language	language	NOUN
fcis-6362	10	7	processing	processing	NOUN
fcis-6362	10	8	can	can	AUX
fcis-6362	10	9	be	be	AUX
fcis-6362	10	10	traced	trace	VERB
fcis-6362	10	11	back	back	ADV
fcis-6362	10	12	to	to	ADP
fcis-6362	10	13	the	the	DET
fcis-6362	10	14	1950s	1950s	NUM
fcis-6362	10	15	.	.	PUNCT
fcis-6362	11	1	during	during	ADP
fcis-6362	11	2	this	this	DET
fcis-6362	11	3	period	period	NOUN
fcis-6362	11	4	,	,	PUNCT
fcis-6362	11	5	computer	computer	NOUN
fcis-6362	11	6	scientists	scientist	NOUN
fcis-6362	11	7	began	begin	VERB
fcis-6362	11	8	using	use	VERB
fcis-6362	11	9	limited	limited	ADJ
fcis-6362	11	10	grammar	grammar	NOUN
fcis-6362	11	11	rules	rule	NOUN
fcis-6362	11	12	and	and	CCONJ
fcis-6362	11	13	dictionaries	dictionary	NOUN
fcis-6362	11	14	to	to	PART
fcis-6362	11	15	attempt	attempt	VERB
fcis-6362	11	16	to	to	PART
fcis-6362	11	17	solve	solve	VERB
fcis-6362	11	18	natural	natural	ADJ
fcis-6362	11	19	language	language	NOUN
fcis-6362	11	20	processing	processing	NOUN
fcis-6362	11	21	problems	problem	NOUN
fcis-6362	11	22	.	.	PUNCT
fcis-6362	12	1	linguist	linguist	NOUN
fcis-6362	12	2	noam	noam	PROPN
fcis-6362	12	3	chomsky	chomsky	PROPN
fcis-6362	13	1	[	[	X
fcis-6362	13	2	1	1	X
fcis-6362	13	3	]	]	PUNCT
fcis-6362	13	4	proposed	propose	VERB
fcis-6362	13	5	chomsky	chomsky	PROPN
fcis-6362	13	6	's	's	PART
fcis-6362	13	7	grammar	grammar	NOUN
fcis-6362	13	8	in	in	ADP
fcis-6362	13	9	1956	1956	NUM
fcis-6362	13	10	,	,	PUNCT
fcis-6362	13	11	which	which	PRON
fcis-6362	13	12	includes	include	VERB
fcis-6362	13	13	four	four	NUM
fcis-6362	13	14	levels	level	NOUN
fcis-6362	13	15	:	:	PUNCT
fcis-6362	13	16	type	type	NOUN
fcis-6362	13	17	0	0	NUM
fcis-6362	13	18	grammar	grammar	NOUN
fcis-6362	13	19	(	(	PUNCT
fcis-6362	13	20	unrestricted	unrestricted	ADJ
fcis-6362	13	21	grammar	grammar	NOUN
fcis-6362	13	22	)	)	PUNCT
fcis-6362	13	23	,	,	PUNCT
fcis-6362	13	24	type	type	NOUN
fcis-6362	13	25	1	1	NUM
fcis-6362	13	26	grammar	grammar	NOUN
fcis-6362	13	27	(	(	PUNCT
fcis-6362	13	28	context	context	NOUN
fcis-6362	13	29	-	-	PUNCT
fcis-6362	13	30	sensitive	sensitive	ADJ
fcis-6362	13	31	grammar	grammar	NOUN
fcis-6362	13	32	)	)	PUNCT
fcis-6362	13	33	,	,	PUNCT
fcis-6362	13	34	type	type	NOUN
fcis-6362	13	35	2	2	NUM
fcis-6362	13	36	grammar	grammar	NOUN
fcis-6362	13	37	(	(	PUNCT
fcis-6362	13	38	context	context	NOUN
fcis-6362	13	39	-	-	PUNCT
fcis-6362	13	40	free	free	ADJ
fcis-6362	13	41	grammar	grammar	NOUN
fcis-6362	13	42	)	)	PUNCT
fcis-6362	13	43	,	,	PUNCT
fcis-6362	13	44	and	and	CCONJ
fcis-6362	13	45	type	type	NOUN
fcis-6362	13	46	3	3	NUM
fcis-6362	13	47	grammar	grammar	NOUN
fcis-6362	13	48	(	(	PUNCT
fcis-6362	13	49	regular	regular	ADJ
fcis-6362	13	50	grammar	grammar	NOUN
fcis-6362	13	51	)	)	PUNCT
fcis-6362	13	52	.	.	PUNCT
fcis-6362	14	1	the	the	DET
fcis-6362	14	2	difference	difference	NOUN
fcis-6362	14	3	between	between	ADP
fcis-6362	14	4	these	these	DET
fcis-6362	14	5	grammar	grammar	NOUN
fcis-6362	14	6	levels	level	NOUN
fcis-6362	14	7	lies	lie	VERB
fcis-6362	14	8	in	in	ADP
fcis-6362	14	9	the	the	DET
fcis-6362	14	10	complexity	complexity	NOUN
fcis-6362	14	11	of	of	ADP
fcis-6362	14	12	the	the	DET
fcis-6362	14	13	language	language	NOUN
fcis-6362	14	14	rules	rule	NOUN
fcis-6362	14	15	they	they	PRON
fcis-6362	14	16	describe	describe	VERB
fcis-6362	14	17	.	.	PUNCT
fcis-6362	15	1	chomsky	chomsky	PROPN
fcis-6362	15	2	's	's	PART
fcis-6362	15	3	grammar	grammar	NOUN
fcis-6362	15	4	is	be	AUX
fcis-6362	15	5	important	important	ADJ
fcis-6362	15	6	for	for	ADP
fcis-6362	15	7	the	the	DET
fcis-6362	15	8	field	field	NOUN
fcis-6362	15	9	of	of	ADP
fcis-6362	15	10	natural	natural	ADJ
fcis-6362	15	11	language	language	NOUN
fcis-6362	15	12	processing	processing	NOUN
fcis-6362	15	13	because	because	SCONJ
fcis-6362	15	14	it	it	PRON
fcis-6362	15	15	provides	provide	VERB
fcis-6362	15	16	a	a	DET
fcis-6362	15	17	formal	formal	ADJ
fcis-6362	15	18	grammar	grammar	NOUN
fcis-6362	15	19	description	description	NOUN
fcis-6362	15	20	method	method	NOUN
fcis-6362	15	21	.	.	PUNCT
fcis-6362	16	1	however	however	ADV
fcis-6362	16	2	,	,	PUNCT
fcis-6362	16	3	due	due	ADP
fcis-6362	16	4	to	to	ADP
fcis-6362	16	5	the	the	DET
fcis-6362	16	6	complexity	complexity	NOUN
fcis-6362	16	7	and	and	CCONJ
fcis-6362	16	8	diversity	diversity	NOUN
fcis-6362	16	9	of	of	ADP
fcis-6362	16	10	language	language	NOUN
fcis-6362	16	11	,	,	PUNCT
fcis-6362	16	12	the	the	DET
fcis-6362	16	13	method	method	NOUN
fcis-6362	16	14	based	base	VERB
fcis-6362	16	15	on	on	ADP
fcis-6362	16	16	limited	limited	ADJ
fcis-6362	16	17	grammar	grammar	NOUN
fcis-6362	16	18	rules	rule	NOUN
fcis-6362	16	19	quickly	quickly	ADV
fcis-6362	16	20	encountered	encounter	VERB
fcis-6362	16	21	bottlenecks	bottleneck	NOUN
fcis-6362	16	22	.	.	PUNCT
fcis-6362	17	1	in	in	ADP
fcis-6362	17	2	the	the	DET
fcis-6362	17	3	1980s	1980	NOUN
fcis-6362	17	4	,	,	PUNCT
fcis-6362	17	5	with	with	ADP
fcis-6362	17	6	the	the	DET
fcis-6362	17	7	introduction	introduction	NOUN
fcis-6362	17	8	of	of	ADP
fcis-6362	17	9	statistical	statistical	ADJ
fcis-6362	17	10	and	and	CCONJ
fcis-6362	17	11	probabilistic	probabilistic	ADJ
fcis-6362	17	12	models	model	NOUN
fcis-6362	17	13	,	,	PUNCT
fcis-6362	17	14	natural	natural	ADJ
fcis-6362	17	15	language	language	NOUN
fcis-6362	17	16	processing	processing	NOUN
fcis-6362	17	17	underwent	underwent	NOUN
fcis-6362	17	18	a	a	DET
fcis-6362	17	19	significant	significant	ADJ
fcis-6362	17	20	transformation	transformation	NOUN
fcis-6362	17	21	.	.	PUNCT
fcis-6362	18	1	machine	machine	NOUN
fcis-6362	18	2	learning	learn	VERB
fcis-6362	18	3	language	language	NOUN
fcis-6362	18	4	models	model	NOUN
fcis-6362	18	5	based	base	VERB
fcis-6362	18	6	on	on	ADP
fcis-6362	18	7	statistics	statistic	NOUN
fcis-6362	18	8	and	and	CCONJ
fcis-6362	18	9	probability	probability	NOUN
fcis-6362	18	10	used	use	VERB
fcis-6362	18	11	large	large	ADJ
fcis-6362	18	12	-	-	PUNCT
fcis-6362	18	13	scale	scale	NOUN
fcis-6362	18	14	corpora	corpora	NOUN
fcis-6362	18	15	to	to	PART
fcis-6362	18	16	train	train	NOUN
fcis-6362	18	17	models	model	NOUN
fcis-6362	18	18	,	,	PUNCT
fcis-6362	18	19	allowing	allow	VERB
fcis-6362	18	20	them	they	PRON
fcis-6362	18	21	to	to	PART
fcis-6362	18	22	better	well	ADV
fcis-6362	18	23	understand	understand	VERB
fcis-6362	18	24	and	and	CCONJ
fcis-6362	18	25	generate	generate	VERB
fcis-6362	18	26	natural	natural	ADJ
fcis-6362	18	27	language	language	NOUN
fcis-6362	18	28	.	.	PUNCT
fcis-6362	19	1	naive	naive	ADJ
fcis-6362	19	2	bayes	bayes	PROPN
fcis-6362	19	3	is	be	AUX
fcis-6362	19	4	a	a	DET
fcis-6362	19	5	machine	machine	NOUN
fcis-6362	19	6	learning	learn	VERB
fcis-6362	19	7	algorithm	algorithm	NOUN
fcis-6362	19	8	based	base	VERB
fcis-6362	19	9	on	on	ADP
fcis-6362	19	10	bayes	bayes	PROPN
fcis-6362	19	11	'	'	PART
fcis-6362	19	12	theorem	theorem	NOUN
fcis-6362	19	13	and	and	CCONJ
fcis-6362	19	14	the	the	DET
fcis-6362	19	15	assumption	assumption	NOUN
fcis-6362	19	16	of	of	ADP
fcis-6362	19	17	feature	feature	NOUN
fcis-6362	19	18	independence	independence	NOUN
fcis-6362	19	19	.	.	PUNCT
fcis-6362	20	1	assuming	assume	VERB
fcis-6362	20	2	that	that	SCONJ
fcis-6362	20	3	the	the	DET
fcis-6362	20	4	impact	impact	NOUN
fcis-6362	20	5	of	of	ADP
fcis-6362	20	6	each	each	DET
fcis-6362	20	7	feature	feature	NOUN
fcis-6362	20	8	on	on	ADP
fcis-6362	20	9	the	the	DET
fcis-6362	20	10	classification	classification	NOUN
fcis-6362	20	11	result	result	NOUN
fcis-6362	20	12	is	be	AUX
fcis-6362	20	13	independent	independent	ADJ
fcis-6362	20	14	of	of	ADP
fcis-6362	20	15	each	each	DET
fcis-6362	20	16	other	other	ADJ
fcis-6362	20	17	simplifies	simplifie	NOUN
fcis-6362	20	18	the	the	DET
fcis-6362	20	19	model	model	NOUN
fcis-6362	20	20	,	,	PUNCT
fcis-6362	20	21	making	make	VERB
fcis-6362	20	22	training	training	NOUN
fcis-6362	20	23	and	and	CCONJ
fcis-6362	20	24	prediction	prediction	NOUN
fcis-6362	20	25	more	more	ADV
fcis-6362	20	26	efficient	efficient	ADJ
fcis-6362	20	27	.	.	PUNCT
fcis-6362	21	1	naive	naive	ADJ
fcis-6362	21	2	bayes	bayes	NOUN
fcis-6362	21	3	classification	classification	NOUN
fcis-6362	21	4	algorithm	algorithm	NOUN
fcis-6362	21	5	performs	perform	VERB
fcis-6362	21	6	extremely	extremely	ADV
fcis-6362	21	7	well	well	ADV
fcis-6362	21	8	in	in	ADP
fcis-6362	21	9	spam	spam	NOUN
fcis-6362	21	10	email	email	NOUN
fcis-6362	21	11	classification	classification	NOUN
fcis-6362	21	12	,	,	PUNCT
fcis-6362	21	13	effectively	effectively	ADV
fcis-6362	21	14	identifying	identify	VERB
fcis-6362	21	15	and	and	CCONJ
fcis-6362	21	16	filtering	filter	VERB
fcis-6362	21	17	a	a	DET
fcis-6362	21	18	large	large	ADJ
fcis-6362	21	19	amount	amount	NOUN
fcis-6362	21	20	of	of	ADP
fcis-6362	21	21	spam	spam	NOUN
fcis-6362	21	22	emails	email	NOUN
fcis-6362	21	23	.	.	PUNCT
fcis-6362	22	1	support	support	NOUN
fcis-6362	22	2	vector	vector	NOUN
fcis-6362	22	3	machine	machine	NOUN
fcis-6362	22	4	(	(	PUNCT
fcis-6362	22	5	svm)[2	svm)[2	PROPN
fcis-6362	22	6	]	]	X
fcis-6362	22	7	is	be	AUX
fcis-6362	22	8	a	a	DET
fcis-6362	22	9	commonly	commonly	ADV
fcis-6362	22	10	used	use	VERB
fcis-6362	22	11	machine	machine	NOUN
fcis-6362	22	12	learning	learn	VERB
fcis-6362	22	13	algorithm	algorithm	NOUN
fcis-6362	22	14	that	that	PRON
fcis-6362	22	15	can	can	AUX
fcis-6362	22	16	be	be	AUX
fcis-6362	22	17	used	use	VERB
fcis-6362	22	18	for	for	ADP
fcis-6362	22	19	classification	classification	NOUN
fcis-6362	22	20	,	,	PUNCT
fcis-6362	22	21	regression	regression	NOUN
fcis-6362	22	22	,	,	PUNCT
fcis-6362	22	23	and	and	CCONJ
fcis-6362	22	24	anomaly	anomaly	NOUN
fcis-6362	22	25	detection	detection	NOUN
fcis-6362	22	26	tasks	task	NOUN
fcis-6362	22	27	.	.	PUNCT
fcis-6362	23	1	in	in	ADP
fcis-6362	23	2	text	text	NOUN
fcis-6362	23	3	classification	classification	NOUN
fcis-6362	23	4	,	,	PUNCT
fcis-6362	23	5	svm	svm	PROPN
fcis-6362	23	6	was	be	AUX
fcis-6362	23	7	initially	initially	ADV
fcis-6362	23	8	used	use	VERB
fcis-6362	23	9	for	for	ADP
fcis-6362	23	10	binary	binary	ADJ
fcis-6362	23	11	classification	classification	NOUN
fcis-6362	23	12	problems	problem	NOUN
fcis-6362	23	13	and	and	CCONJ
fcis-6362	23	14	can	can	AUX
fcis-6362	23	15	be	be	AUX
fcis-6362	23	16	extended	extend	VERB
fcis-6362	23	17	to	to	ADP
fcis-6362	23	18	multiclass	multiclass	ADJ
fcis-6362	23	19	classification	classification	NOUN
fcis-6362	23	20	using	use	VERB
fcis-6362	23	21	the	the	DET
fcis-6362	23	22	one	one	NUM
fcis-6362	23	23	-	-	PUNCT
fcis-6362	23	24	vs	vs	ADP
fcis-6362	23	25	-	-	PUNCT
fcis-6362	23	26	all	all	PRON
fcis-6362	23	27	or	or	CCONJ
fcis-6362	23	28	one	one	NUM
fcis-6362	23	29	-	-	PUNCT
fcis-6362	23	30	vs	vs	ADP
fcis-6362	23	31	-	-	PUNCT
fcis-6362	23	32	one	one	NUM
fcis-6362	23	33	approach	approach	NOUN
fcis-6362	23	34	.	.	PUNCT
fcis-6362	24	1	hidden	hide	VERB
fcis-6362	24	2	markov	markov	NOUN
fcis-6362	24	3	model	model	NOUN
fcis-6362	24	4	(	(	PUNCT
fcis-6362	24	5	hmm)[3	hmm)[3	PROPN
fcis-6362	24	6	]	]	PUNCT
fcis-6362	24	7	is	be	AUX
fcis-6362	24	8	a	a	DET
fcis-6362	24	9	probabilistic	probabilistic	ADJ
fcis-6362	24	10	model	model	NOUN
fcis-6362	24	11	based	base	VERB
fcis-6362	24	12	on	on	ADP
fcis-6362	24	13	state	state	NOUN
fcis-6362	24	14	transitions	transition	NOUN
fcis-6362	24	15	that	that	PRON
fcis-6362	24	16	can	can	AUX
fcis-6362	24	17	consider	consider	VERB
fcis-6362	24	18	contextual	contextual	ADJ
fcis-6362	24	19	information	information	NOUN
fcis-6362	24	20	and	and	CCONJ
fcis-6362	24	21	predict	predict	VERB
fcis-6362	24	22	the	the	DET
fcis-6362	24	23	next	next	ADJ
fcis-6362	24	24	state	state	NOUN
fcis-6362	24	25	based	base	VERB
fcis-6362	24	26	on	on	ADP
fcis-6362	24	27	the	the	DET
fcis-6362	24	28	previous	previous	ADJ
fcis-6362	24	29	state	state	NOUN
fcis-6362	24	30	,	,	PUNCT
fcis-6362	24	31	commonly	commonly	ADV
fcis-6362	24	32	used	use	VERB
fcis-6362	24	33	for	for	ADP
fcis-6362	24	34	the	the	DET
fcis-6362	24	35	conversion	conversion	NOUN
fcis-6362	24	36	between	between	ADP
fcis-6362	24	37	speech	speech	NOUN
fcis-6362	24	38	and	and	CCONJ
fcis-6362	24	39	text	text	NOUN
fcis-6362	24	40	.	.	PUNCT
fcis-6362	25	1	deep	deep	ADJ
fcis-6362	25	2	learning	learn	VERB
fcis-6362	25	3	originates	originate	NOUN
fcis-6362	25	4	from	from	ADP
fcis-6362	25	5	the	the	DET
fcis-6362	25	6	neural	neural	ADJ
fcis-6362	25	7	network	network	NOUN
fcis-6362	25	8	structure	structure	NOUN
fcis-6362	25	9	in	in	ADP
fcis-6362	25	10	machine	machine	NOUN
fcis-6362	25	11	learning	learning	NOUN
fcis-6362	25	12	,	,	PUNCT
fcis-6362	25	13	which	which	PRON
fcis-6362	25	14	enables	enable	VERB
fcis-6362	25	15	the	the	DET
fcis-6362	25	16	learning	learning	NOUN
fcis-6362	25	17	of	of	ADP
fcis-6362	25	18	more	more	ADJ
fcis-6362	25	19	complex	complex	ADJ
fcis-6362	25	20	expressions	expression	NOUN
fcis-6362	25	21	and	and	CCONJ
fcis-6362	25	22	features	feature	NOUN
fcis-6362	25	23	from	from	ADP
fcis-6362	25	24	raw	raw	ADJ
fcis-6362	25	25	data	datum	NOUN
fcis-6362	25	26	by	by	ADP
fcis-6362	25	27	constructing	construct	VERB
fcis-6362	25	28	multiple	multiple	ADJ
fcis-6362	25	29	levels	level	NOUN
fcis-6362	25	30	of	of	ADP
fcis-6362	25	31	abstract	abstract	ADJ
fcis-6362	25	32	feature	feature	NOUN
fcis-6362	25	33	representations	representation	NOUN
fcis-6362	25	34	to	to	PART
fcis-6362	25	35	improve	improve	VERB
fcis-6362	25	36	the	the	DET
fcis-6362	25	37	accuracy	accuracy	NOUN
fcis-6362	25	38	of	of	ADP
fcis-6362	25	39	prediction	prediction	NOUN
fcis-6362	25	40	and	and	CCONJ
fcis-6362	25	41	classification	classification	NOUN
fcis-6362	25	42	.	.	PUNCT
fcis-6362	26	1	in	in	ADP
fcis-6362	26	2	recent	recent	ADJ
fcis-6362	26	3	years	year	NOUN
fcis-6362	26	4	,	,	PUNCT
fcis-6362	26	5	deep	deep	ADJ
fcis-6362	26	6	learning	learning	NOUN
fcis-6362	26	7	has	have	AUX
fcis-6362	26	8	rapidly	rapidly	ADV
fcis-6362	26	9	developed	develop	VERB
fcis-6362	26	10	from	from	ADP
fcis-6362	26	11	a	a	DET
fcis-6362	26	12	branch	branch	NOUN
fcis-6362	26	13	of	of	ADP
fcis-6362	26	14	traditional	traditional	ADJ
fcis-6362	26	15	machine	machine	NOUN
fcis-6362	26	16	learning	learn	VERB
fcis-6362	26	17	to	to	ADP
fcis-6362	26	18	a	a	DET
fcis-6362	26	19	mainstream	mainstream	NOUN
fcis-6362	26	20	method	method	NOUN
fcis-6362	26	21	.	.	PUNCT
fcis-6362	27	1	the	the	DET
fcis-6362	27	2	growth	growth	NOUN
fcis-6362	27	3	of	of	ADP
fcis-6362	27	4	gpu	gpu	NOUN
fcis-6362	27	5	computing	computing	NOUN
fcis-6362	27	6	power	power	NOUN
fcis-6362	27	7	in	in	ADP
fcis-6362	27	8	recent	recent	ADJ
fcis-6362	27	9	years	year	NOUN
fcis-6362	27	10	has	have	AUX
fcis-6362	27	11	greatly	greatly	ADV
fcis-6362	27	12	improved	improve	VERB
fcis-6362	27	13	the	the	DET
fcis-6362	27	14	training	training	NOUN
fcis-6362	27	15	and	and	CCONJ
fcis-6362	27	16	inference	inference	NOUN
fcis-6362	27	17	speed	speed	NOUN
fcis-6362	27	18	of	of	ADP
fcis-6362	27	19	neural	neural	ADJ
fcis-6362	27	20	network	network	NOUN
fcis-6362	27	21	models	model	NOUN
fcis-6362	27	22	,	,	PUNCT
fcis-6362	27	23	allowing	allow	VERB
fcis-6362	27	24	for	for	ADP
fcis-6362	27	25	the	the	DET
fcis-6362	27	26	implementation	implementation	NOUN
fcis-6362	27	27	and	and	CCONJ
fcis-6362	27	28	application	application	NOUN
fcis-6362	27	29	of	of	ADP
fcis-6362	27	30	larger	large	ADJ
fcis-6362	27	31	and	and	CCONJ
fcis-6362	27	32	more	more	ADV
fcis-6362	27	33	complex	complex	ADJ
fcis-6362	27	34	models	model	NOUN
fcis-6362	27	35	.	.	PUNCT
fcis-6362	28	1	the	the	DET
fcis-6362	28	2	development	development	NOUN
fcis-6362	28	3	of	of	ADP
fcis-6362	28	4	deep	deep	ADJ
fcis-6362	28	5	learning	learning	NOUN
fcis-6362	28	6	in	in	ADP
fcis-6362	28	7	natural	natural	ADJ
fcis-6362	28	8	language	language	NOUN
fcis-6362	28	9	processing	processing	NOUN
fcis-6362	28	10	can	can	AUX
fcis-6362	28	11	also	also	ADV
fcis-6362	28	12	be	be	AUX
fcis-6362	28	13	divided	divide	VERB
fcis-6362	28	14	into	into	ADP
fcis-6362	28	15	several	several	ADJ
fcis-6362	28	16	stages	stage	NOUN
fcis-6362	28	17	.	.	PUNCT
fcis-6362	29	1	early	early	ADJ
fcis-6362	29	2	work	work	NOUN
fcis-6362	29	3	(	(	PUNCT
fcis-6362	29	4	2000	2000	NUM
fcis-6362	29	5	to	to	ADP
fcis-6362	29	6	2016	2016	NUM
fcis-6362	29	7	)	)	PUNCT
fcis-6362	29	8	focused	focus	VERB
fcis-6362	29	9	on	on	ADP
fcis-6362	29	10	unsupervised	unsupervised	ADJ
fcis-6362	29	11	vectorization	vectorization	NOUN
fcis-6362	29	12	of	of	ADP
fcis-6362	29	13	words	word	NOUN
fcis-6362	29	14	and	and	CCONJ
fcis-6362	29	15	structural	structural	ADJ
fcis-6362	29	16	engineering	engineering	NOUN
fcis-6362	29	17	of	of	ADP
fcis-6362	29	18	networks	network	NOUN
fcis-6362	29	19	.	.	PUNCT
fcis-6362	30	1	the	the	DET
fcis-6362	30	2	bag	bag	NOUN
fcis-6362	30	3	-	-	PUNCT
fcis-6362	30	4	ofwords	ofword	NOUN
fcis-6362	30	5	model	model	NOUN
fcis-6362	30	6	(	(	PUNCT
fcis-6362	30	7	bow)[4	bow)[4	NOUN
fcis-6362	30	8	]	]	PUNCT
fcis-6362	30	9	was	be	AUX
fcis-6362	30	10	originally	originally	ADV
fcis-6362	30	11	used	use	VERB
fcis-6362	30	12	in	in	ADP
fcis-6362	30	13	text	text	NOUN
fcis-6362	30	14	classification	classification	NOUN
fcis-6362	30	15	.	.	PUNCT
fcis-6362	31	1	this	this	DET
fcis-6362	31	2	model	model	NOUN
fcis-6362	31	3	treats	treat	VERB
fcis-6362	31	4	each	each	DET
fcis-6362	31	5	word	word	NOUN
fcis-6362	31	6	in	in	ADP
fcis-6362	31	7	the	the	DET
fcis-6362	31	8	text	text	NOUN
fcis-6362	31	9	as	as	ADP
fcis-6362	31	10	an	an	DET
fcis-6362	31	11	independent	independent	ADJ
fcis-6362	31	12	feature	feature	NOUN
fcis-6362	31	13	and	and	CCONJ
fcis-6362	31	14	represents	represent	VERB
fcis-6362	31	15	the	the	DET
fcis-6362	31	16	document	document	NOUN
fcis-6362	31	17	as	as	ADP
fcis-6362	31	18	a	a	DET
fcis-6362	31	19	feature	feature	NOUN
fcis-6362	31	20	vector	vector	NOUN
fcis-6362	31	21	.	.	PUNCT
fcis-6362	32	1	the	the	DET
fcis-6362	32	2	basic	basic	ADJ
fcis-6362	32	3	idea	idea	NOUN
fcis-6362	32	4	is	be	AUX
fcis-6362	32	5	to	to	PART
fcis-6362	32	6	assume	assume	VERB
fcis-6362	32	7	that	that	SCONJ
fcis-6362	32	8	for	for	ADP
fcis-6362	32	9	a	a	DET
fcis-6362	32	10	text	text	NOUN
fcis-6362	32	11	,	,	PUNCT
fcis-6362	32	12	its	its	PRON
fcis-6362	32	13	word	word	NOUN
fcis-6362	32	14	order	order	NOUN
fcis-6362	32	15	and	and	CCONJ
fcis-6362	32	16	grammar	grammar	NOUN
fcis-6362	32	17	syntax	syntax	NOUN
fcis-6362	32	18	can	can	AUX
fcis-6362	32	19	be	be	AUX
fcis-6362	32	20	ignored	ignore	VERB
fcis-6362	32	21	,	,	PUNCT
fcis-6362	32	22	and	and	CCONJ
fcis-6362	32	23	it	it	PRON
fcis-6362	32	24	can	can	AUX
fcis-6362	32	25	be	be	AUX
fcis-6362	32	26	regarded	regard	VERB
fcis-6362	32	27	as	as	ADP
fcis-6362	32	28	a	a	DET
fcis-6362	32	29	collection	collection	NOUN
fcis-6362	32	30	of	of	ADP
fcis-6362	32	31	vocabulary	vocabulary	NOUN
fcis-6362	32	32	.	.	PUNCT
fcis-6362	33	1	each	each	DET
fcis-6362	33	2	vocabulary	vocabulary	NOUN
fcis-6362	33	3	in	in	ADP
fcis-6362	33	4	the	the	DET
fcis-6362	33	5	text	text	NOUN
fcis-6362	33	6	is	be	AUX
fcis-6362	33	7	an	an	DET
fcis-6362	33	8	independent	independent	ADJ
fcis-6362	33	9	feature	feature	NOUN
fcis-6362	33	10	.	.	PUNCT
fcis-6362	34	1	n	n	CCONJ
fcis-6362	34	2	-	-	PUNCT
fcis-6362	34	3	gram	gram	NOUN
fcis-6362	35	1	[	[	X
fcis-6362	35	2	5	5	NUM
fcis-6362	35	3	]	]	PUNCT
fcis-6362	35	4	is	be	AUX
fcis-6362	35	5	an	an	DET
fcis-6362	35	6	algorithm	algorithm	NOUN
fcis-6362	35	7	based	base	VERB
fcis-6362	35	8	on	on	ADP
fcis-6362	35	9	statistical	statistical	ADJ
fcis-6362	35	10	language	language	NOUN
fcis-6362	35	11	model	model	NOUN
fcis-6362	35	12	.	.	PUNCT
fcis-6362	36	1	its	its	PRON
fcis-6362	36	2	basic	basic	ADJ
fcis-6362	36	3	idea	idea	NOUN
fcis-6362	36	4	is	be	AUX
fcis-6362	36	5	to	to	PART
fcis-6362	36	6	slide	slide	VERB
fcis-6362	36	7	a	a	DET
fcis-6362	36	8	window	window	NOUN
fcis-6362	36	9	of	of	ADP
fcis-6362	36	10	size	size	NOUN
fcis-6362	36	11	n	n	CCONJ
fcis-6362	36	12	over	over	ADP
fcis-6362	36	13	the	the	DET
fcis-6362	36	14	text	text	NOUN
fcis-6362	36	15	,	,	PUNCT
fcis-6362	36	16	which	which	PRON
fcis-6362	36	17	is	be	AUX
fcis-6362	36	18	segmented	segment	VERB
fcis-6362	36	19	into	into	ADP
fcis-6362	36	20	byte	byte	NOUN
fcis-6362	36	21	fragments	fragment	NOUN
fcis-6362	36	22	,	,	PUNCT
fcis-6362	36	23	to	to	PART
fcis-6362	36	24	form	form	VERB
fcis-6362	36	25	a	a	DET
fcis-6362	36	26	sequence	sequence	NOUN
fcis-6362	36	27	of	of	ADP
fcis-6362	36	28	byte	byte	NOUN
fcis-6362	36	29	fragments	fragment	NOUN
fcis-6362	36	30	with	with	ADP
fcis-6362	36	31	a	a	DET
fcis-6362	36	32	length	length	NOUN
fcis-6362	36	33	of	of	ADP
fcis-6362	36	34	n.	n.	NOUN
fcis-6362	36	35	each	each	DET
fcis-6362	36	36	byte	byte	NOUN
fcis-6362	36	37	fragment	fragment	NOUN
fcis-6362	36	38	is	be	AUX
fcis-6362	36	39	called	call	VERB
fcis-6362	36	40	a	a	DET
fcis-6362	36	41	gram	gram	NOUN
fcis-6362	36	42	.	.	PUNCT
fcis-6362	37	1	by	by	ADP
fcis-6362	37	2	counting	count	VERB
fcis-6362	37	3	the	the	DET
fcis-6362	37	4	frequency	frequency	NOUN
fcis-6362	37	5	of	of	ADP
fcis-6362	37	6	occurrence	occurrence	NOUN
fcis-6362	37	7	of	of	ADP
fcis-6362	37	8	all	all	DET
fcis-6362	37	9	grams	gram	NOUN
fcis-6362	37	10	and	and	CCONJ
fcis-6362	37	11	filtering	filter	VERB
fcis-6362	37	12	them	they	PRON
fcis-6362	37	13	according	accord	VERB
fcis-6362	37	14	to	to	ADP
fcis-6362	37	15	a	a	DET
fcis-6362	37	16	pre	pre	ADJ
fcis-6362	37	17	-	-	ADJ
fcis-6362	37	18	set	set	ADJ
fcis-6362	37	19	threshold	threshold	NOUN
fcis-6362	37	20	,	,	PUNCT
fcis-6362	37	21	a	a	DET
fcis-6362	37	22	key	key	ADJ
fcis-6362	37	23	gram	gram	NOUN
fcis-6362	37	24	list	list	NOUN
fcis-6362	37	25	is	be	AUX
fcis-6362	37	26	formed	form	VERB
fcis-6362	37	27	,	,	PUNCT
fcis-6362	37	28	which	which	PRON
fcis-6362	37	29	is	be	AUX
fcis-6362	37	30	the	the	DET
fcis-6362	37	31	vector	vector	NOUN
fcis-6362	37	32	feature	feature	NOUN
fcis-6362	37	33	space	space	NOUN
fcis-6362	37	34	of	of	ADP
fcis-6362	37	35	the	the	DET
fcis-6362	37	36	text	text	NOUN
fcis-6362	37	37	.	.	PUNCT
fcis-6362	38	1	each	each	DET
fcis-6362	38	2	gram	gram	NOUN
fcis-6362	38	3	in	in	ADP
fcis-6362	38	4	the	the	DET
fcis-6362	38	5	list	list	NOUN
fcis-6362	38	6	is	be	AUX
fcis-6362	38	7	a	a	DET
fcis-6362	38	8	feature	feature	NOUN
fcis-6362	38	9	vector	vector	NOUN
fcis-6362	38	10	dimension	dimension	NOUN
fcis-6362	38	11	.	.	PUNCT
fcis-6362	39	1	from	from	ADP
fcis-6362	39	2	2017	2017	NUM
fcis-6362	39	3	to	to	ADP
fcis-6362	39	4	2019	2019	NUM
fcis-6362	39	5	,	,	PUNCT
fcis-6362	39	6	there	there	PRON
fcis-6362	39	7	were	be	VERB
fcis-6362	39	8	significant	significant	ADJ
fcis-6362	39	9	changes	change	NOUN
fcis-6362	39	10	in	in	ADP
fcis-6362	39	11	the	the	DET
fcis-6362	39	12	learning	learning	NOUN
fcis-6362	39	13	of	of	ADP
fcis-6362	39	14	nlp	nlp	NOUN
fcis-6362	39	15	models	model	NOUN
fcis-6362	39	16	,	,	PUNCT
fcis-6362	39	17	and	and	CCONJ
fcis-6362	39	18	the	the	DET
fcis-6362	39	19	completely	completely	ADV
fcis-6362	39	20	supervised	supervised	ADJ
fcis-6362	39	21	paradigm	paradigm	NOUN
fcis-6362	39	22	is	be	AUX
fcis-6362	39	23	now	now	ADV
fcis-6362	39	24	playing	play	VERB
fcis-6362	39	25	a	a	DET
fcis-6362	39	26	decreasing	decrease	VERB
fcis-6362	39	27	role	role	NOUN
fcis-6362	39	28	.	.	PUNCT
fcis-6362	40	1	specifically	specifically	ADV
fcis-6362	40	2	,	,	PUNCT
fcis-6362	40	3	the	the	DET
fcis-6362	40	4	standard	standard	NOUN
fcis-6362	40	5	has	have	AUX
fcis-6362	40	6	shifted	shift	VERB
fcis-6362	40	7	towards	towards	ADP
fcis-6362	40	8	168	168	NUM
fcis-6362	40	9	pre	pre	ADJ
fcis-6362	40	10	-	-	ADJ
fcis-6362	40	11	training	training	ADJ
fcis-6362	40	12	and	and	CCONJ
fcis-6362	40	13	fine	fine	ADV
fcis-6362	40	14	-	-	PUNCT
fcis-6362	40	15	tuning	tuning	NOUN
fcis-6362	40	16	paradigms	paradigm	NOUN
fcis-6362	40	17	.	.	PUNCT
fcis-6362	41	1	in	in	ADP
fcis-6362	41	2	this	this	DET
fcis-6362	41	3	paradigm	paradigm	NOUN
fcis-6362	41	4	,	,	PUNCT
fcis-6362	41	5	models	model	NOUN
fcis-6362	41	6	with	with	ADP
fcis-6362	41	7	fixed	fix	VERB
fcis-6362	41	8	architectures	architecture	NOUN
fcis-6362	41	9	are	be	AUX
fcis-6362	41	10	pre	pre	ADJ
fcis-6362	41	11	-	-	VERB
fcis-6362	41	12	trained	train	VERB
fcis-6362	41	13	as	as	ADP
fcis-6362	41	14	language	language	NOUN
fcis-6362	41	15	models	model	NOUN
fcis-6362	41	16	(	(	PUNCT
fcis-6362	41	17	lms	lm	NOUN
fcis-6362	41	18	)	)	PUNCT
fcis-6362	41	19	to	to	PART
fcis-6362	41	20	predict	predict	VERB
fcis-6362	41	21	the	the	DET
fcis-6362	41	22	probability	probability	NOUN
fcis-6362	41	23	of	of	ADP
fcis-6362	41	24	observed	observed	ADJ
fcis-6362	41	25	textual	textual	ADJ
fcis-6362	41	26	data	datum	NOUN
fcis-6362	41	27	.	.	PUNCT
fcis-6362	42	1	since	since	SCONJ
fcis-6362	42	2	a	a	DET
fcis-6362	42	3	large	large	ADJ
fcis-6362	42	4	amount	amount	NOUN
fcis-6362	42	5	of	of	ADP
fcis-6362	42	6	raw	raw	ADJ
fcis-6362	42	7	text	text	NOUN
fcis-6362	42	8	data	datum	NOUN
fcis-6362	42	9	is	be	AUX
fcis-6362	42	10	required	require	VERB
fcis-6362	42	11	to	to	PART
fcis-6362	42	12	train	train	VERB
fcis-6362	42	13	lms	lm	NOUN
fcis-6362	42	14	,	,	PUNCT
fcis-6362	42	15	these	these	DET
fcis-6362	42	16	lms	lm	NOUN
fcis-6362	42	17	can	can	AUX
fcis-6362	42	18	be	be	AUX
fcis-6362	42	19	trained	train	VERB
fcis-6362	42	20	on	on	ADP
fcis-6362	42	21	large	large	ADJ
fcis-6362	42	22	datasets	dataset	NOUN
fcis-6362	42	23	to	to	PART
fcis-6362	42	24	learn	learn	VERB
fcis-6362	42	25	robust	robust	ADJ
fcis-6362	42	26	and	and	CCONJ
fcis-6362	42	27	general	general	ADJ
fcis-6362	42	28	language	language	NOUN
fcis-6362	42	29	modeling	modeling	NOUN
fcis-6362	42	30	features	feature	NOUN
fcis-6362	42	31	.	.	PUNCT
fcis-6362	43	1	then	then	ADV
fcis-6362	43	2	,	,	PUNCT
fcis-6362	43	3	additional	additional	ADJ
fcis-6362	43	4	parameters	parameter	NOUN
fcis-6362	43	5	are	be	AUX
fcis-6362	43	6	introduced	introduce	VERB
fcis-6362	43	7	,	,	PUNCT
fcis-6362	43	8	and	and	CCONJ
fcis-6362	43	9	task	task	NOUN
fcis-6362	43	10	-	-	PUNCT
fcis-6362	43	11	specific	specific	ADJ
fcis-6362	43	12	objective	objective	ADJ
fcis-6362	43	13	functions	function	NOUN
fcis-6362	43	14	are	be	AUX
fcis-6362	43	15	used	use	VERB
fcis-6362	43	16	to	to	ADP
fcis-6362	43	17	fine	fine	ADJ
fcis-6362	43	18	-	-	PUNCT
fcis-6362	43	19	tune	tune	NOUN
fcis-6362	43	20	the	the	DET
fcis-6362	43	21	aforementioned	aforementioned	ADJ
fcis-6362	43	22	pre	pre	ADJ
fcis-6362	43	23	-	-	ADJ
fcis-6362	43	24	trained	train	VERB
fcis-6362	43	25	lms	lm	NOUN
fcis-6362	43	26	to	to	PART
fcis-6362	43	27	adapt	adapt	VERB
fcis-6362	43	28	to	to	ADP
fcis-6362	43	29	different	different	ADJ
fcis-6362	43	30	downstream	downstream	ADJ
fcis-6362	43	31	tasks	task	NOUN
fcis-6362	43	32	.	.	PUNCT
fcis-6362	44	1	in	in	ADP
fcis-6362	44	2	this	this	DET
fcis-6362	44	3	paradigm	paradigm	NOUN
fcis-6362	44	4	,	,	PUNCT
fcis-6362	44	5	the	the	DET
fcis-6362	44	6	focus	focus	NOUN
fcis-6362	44	7	has	have	AUX
fcis-6362	44	8	mainly	mainly	ADV
fcis-6362	44	9	shifted	shift	VERB
fcis-6362	44	10	to	to	PART
fcis-6362	44	11	target	target	VERB
fcis-6362	44	12	engineering	engineering	NOUN
fcis-6362	44	13	and	and	CCONJ
fcis-6362	44	14	designing	design	VERB
fcis-6362	44	15	training	training	NOUN
fcis-6362	44	16	objectives	objective	NOUN
fcis-6362	44	17	for	for	ADP
fcis-6362	44	18	the	the	DET
fcis-6362	44	19	pretraining	pretraine	VERB
fcis-6362	44	20	and	and	CCONJ
fcis-6362	44	21	fine	fine	ADV
fcis-6362	44	22	-	-	PUNCT
fcis-6362	44	23	tuning	tuning	NOUN
fcis-6362	44	24	stages	stage	NOUN
fcis-6362	44	25	.	.	PUNCT
fcis-6362	45	1	bert	bert	PROPN
fcis-6362	45	2	(	(	PUNCT
fcis-6362	45	3	bidirectional	bidirectional	ADJ
fcis-6362	45	4	encoder	encoder	NOUN
fcis-6362	45	5	representations	representation	VERB
fcis-6362	45	6	from	from	ADP
fcis-6362	45	7	transformers	transformer	NOUN
fcis-6362	45	8	)	)	PUNCT
fcis-6362	46	1	[	[	X
fcis-6362	46	2	6	6	NUM
fcis-6362	46	3	]	]	PUNCT
fcis-6362	46	4	is	be	AUX
fcis-6362	46	5	a	a	DET
fcis-6362	46	6	pre	pre	ADJ
fcis-6362	46	7	-	-	ADJ
fcis-6362	46	8	trained	train	VERB
fcis-6362	46	9	transformer	transformer	NOUN
fcis-6362	46	10	-	-	PUNCT
fcis-6362	46	11	based	base	VERB
fcis-6362	46	12	model	model	NOUN
fcis-6362	46	13	developed	develop	VERB
fcis-6362	46	14	by	by	ADP
fcis-6362	46	15	google	google	PROPN
fcis-6362	46	16	.	.	PUNCT
fcis-6362	47	1	gpt	gpt	PROPN
fcis-6362	47	2	(	(	PUNCT
fcis-6362	47	3	generative	generative	ADJ
fcis-6362	47	4	pre	pre	ADJ
fcis-6362	47	5	-	-	ADJ
fcis-6362	47	6	trained	train	VERB
fcis-6362	47	7	transformer	transformer	NOUN
fcis-6362	47	8	)	)	PUNCT
fcis-6362	48	1	[	[	X
fcis-6362	48	2	7	7	X
fcis-6362	48	3	]	]	PUNCT
fcis-6362	48	4	is	be	AUX
fcis-6362	48	5	a	a	DET
fcis-6362	48	6	pre	pre	ADJ
fcis-6362	48	7	-	-	ADJ
fcis-6362	48	8	trained	train	VERB
fcis-6362	48	9	transformer	transformer	NOUN
fcis-6362	48	10	-	-	PUNCT
fcis-6362	48	11	based	base	VERB
fcis-6362	48	12	model	model	NOUN
fcis-6362	48	13	developed	develop	VERB
fcis-6362	48	14	by	by	ADP
fcis-6362	48	15	openai	openai	NOUN
fcis-6362	48	16	,	,	PUNCT
fcis-6362	48	17	which	which	PRON
fcis-6362	48	18	is	be	AUX
fcis-6362	48	19	trained	train	VERB
fcis-6362	48	20	on	on	ADP
fcis-6362	48	21	a	a	DET
fcis-6362	48	22	large	large	ADJ
fcis-6362	48	23	corpus	corpus	NOUN
fcis-6362	48	24	of	of	ADP
fcis-6362	48	25	text	text	NOUN
fcis-6362	48	26	to	to	PART
fcis-6362	48	27	generate	generate	VERB
fcis-6362	48	28	high	high	ADJ
fcis-6362	48	29	-	-	PUNCT
fcis-6362	48	30	quality	quality	NOUN
fcis-6362	48	31	language	language	NOUN
fcis-6362	48	32	outputs	output	NOUN
fcis-6362	48	33	such	such	ADJ
fcis-6362	48	34	as	as	ADP
fcis-6362	48	35	text	text	NOUN
fcis-6362	48	36	completion	completion	NOUN
fcis-6362	48	37	,	,	PUNCT
fcis-6362	48	38	summarization	summarization	NOUN
fcis-6362	48	39	,	,	PUNCT
fcis-6362	48	40	and	and	CCONJ
fcis-6362	48	41	translation	translation	NOUN
fcis-6362	48	42	.	.	PUNCT
fcis-6362	49	1	nowadays	nowadays	ADV
fcis-6362	49	2	,	,	PUNCT
fcis-6362	49	3	natural	natural	ADJ
fcis-6362	49	4	language	language	NOUN
fcis-6362	49	5	processing	processing	NOUN
fcis-6362	49	6	is	be	AUX
fcis-6362	49	7	in	in	ADP
fcis-6362	49	8	the	the	DET
fcis-6362	49	9	midst	midst	NOUN
fcis-6362	49	10	of	of	ADP
fcis-6362	49	11	a	a	DET
fcis-6362	49	12	second	second	ADJ
fcis-6362	49	13	major	major	ADJ
fcis-6362	49	14	transformation	transformation	NOUN
fcis-6362	49	15	,	,	PUNCT
fcis-6362	49	16	with	with	ADP
fcis-6362	49	17	the	the	DET
fcis-6362	49	18	"	"	PUNCT
fcis-6362	49	19	pre	pre	ADJ
fcis-6362	49	20	-	-	ADJ
fcis-6362	49	21	train	train	ADJ
fcis-6362	49	22	and	and	CCONJ
fcis-6362	49	23	fine	fine	ADJ
fcis-6362	49	24	-	-	PUNCT
fcis-6362	49	25	tune	tune	NOUN
fcis-6362	49	26	"	"	PUNCT
fcis-6362	49	27	paradigm	paradigm	NOUN
fcis-6362	49	28	being	be	AUX
fcis-6362	49	29	replaced	replace	VERB
fcis-6362	49	30	by	by	ADP
fcis-6362	49	31	what	what	PRON
fcis-6362	49	32	we	we	PRON
fcis-6362	49	33	call	call	VERB
fcis-6362	49	34	the	the	DET
fcis-6362	49	35	"	"	PUNCT
fcis-6362	49	36	pre	pre	ADJ
fcis-6362	49	37	-	-	ADJ
fcis-6362	49	38	train	train	ADJ
fcis-6362	49	39	,	,	PUNCT
fcis-6362	49	40	prompt	prompt	ADJ
fcis-6362	49	41	,	,	PUNCT
fcis-6362	49	42	and	and	CCONJ
fcis-6362	49	43	predict	predict	VERB
fcis-6362	49	44	"	"	PUNCT
fcis-6362	49	45	paradigm	paradigm	NOUN
fcis-6362	49	46	.	.	PUNCT
fcis-6362	50	1	in	in	ADP
fcis-6362	50	2	this	this	DET
fcis-6362	50	3	paradigm	paradigm	NOUN
fcis-6362	50	4	,	,	PUNCT
fcis-6362	50	5	instead	instead	ADV
fcis-6362	50	6	of	of	ADP
fcis-6362	50	7	adapting	adapt	VERB
fcis-6362	50	8	pre	pre	ADJ
fcis-6362	50	9	-	-	ADJ
fcis-6362	50	10	trained	train	VERB
fcis-6362	50	11	lms	lm	NOUN
fcis-6362	50	12	to	to	PART
fcis-6362	50	13	downstream	downstream	VERB
fcis-6362	50	14	tasks	task	NOUN
fcis-6362	50	15	through	through	ADP
fcis-6362	50	16	target	target	NOUN
fcis-6362	50	17	engineering	engineering	NOUN
fcis-6362	50	18	,	,	PUNCT
fcis-6362	50	19	downstream	downstream	ADJ
fcis-6362	50	20	tasks	task	NOUN
fcis-6362	50	21	are	be	AUX
fcis-6362	50	22	reformulated	reformulate	VERB
fcis-6362	50	23	with	with	ADP
fcis-6362	50	24	the	the	DET
fcis-6362	50	25	help	help	NOUN
fcis-6362	50	26	of	of	ADP
fcis-6362	50	27	textual	textual	ADJ
fcis-6362	50	28	prompts	prompt	NOUN
fcis-6362	50	29	to	to	PART
fcis-6362	50	30	resemble	resemble	VERB
fcis-6362	50	31	the	the	DET
fcis-6362	50	32	tasks	task	NOUN
fcis-6362	50	33	solved	solve	VERB
fcis-6362	50	34	during	during	ADP
fcis-6362	50	35	the	the	DET
fcis-6362	50	36	original	original	ADJ
fcis-6362	50	37	lm	lm	ADJ
fcis-6362	50	38	training	training	NOUN
fcis-6362	50	39	.	.	PUNCT
fcis-6362	51	1	for	for	ADP
fcis-6362	51	2	example	example	NOUN
fcis-6362	51	3	,	,	PUNCT
fcis-6362	51	4	when	when	SCONJ
fcis-6362	51	5	identifying	identify	VERB
fcis-6362	51	6	the	the	DET
fcis-6362	51	7	sentiment	sentiment	NOUN
fcis-6362	51	8	of	of	ADP
fcis-6362	51	9	social	social	ADJ
fcis-6362	51	10	media	medium	NOUN
fcis-6362	51	11	posts	post	NOUN
fcis-6362	51	12	,	,	PUNCT
fcis-6362	51	13	for	for	ADP
fcis-6362	51	14	the	the	DET
fcis-6362	51	15	sentence	sentence	NOUN
fcis-6362	51	16	"	"	PUNCT
fcis-6362	51	17	i	i	PRON
fcis-6362	51	18	lost	lose	VERB
fcis-6362	51	19	my	my	PRON
fcis-6362	51	20	wallet	wallet	NOUN
fcis-6362	51	21	today	today	NOUN
fcis-6362	51	22	.	.	PUNCT
fcis-6362	52	1	"	"	PUNCT
fcis-6362	52	2	,	,	PUNCT
fcis-6362	52	3	we	we	PRON
fcis-6362	52	4	can	can	AUX
fcis-6362	52	5	prompt	prompt	VERB
fcis-6362	52	6	the	the	DET
fcis-6362	52	7	lm	lm	NOUN
fcis-6362	52	8	with	with	ADP
fcis-6362	52	9	"	"	PUNCT
fcis-6362	52	10	i	i	PRON
fcis-6362	52	11	feel	feel	VERB
fcis-6362	52	12	_	_	PUNCT
fcis-6362	52	13	_	_	PUNCT
fcis-6362	52	14	"	"	PUNCT
fcis-6362	52	15	and	and	CCONJ
fcis-6362	52	16	ask	ask	VERB
fcis-6362	52	17	it	it	PRON
fcis-6362	52	18	to	to	PART
fcis-6362	52	19	fill	fill	VERB
fcis-6362	52	20	in	in	ADP
fcis-6362	52	21	the	the	DET
fcis-6362	52	22	blank	blank	NOUN
fcis-6362	52	23	with	with	ADP
fcis-6362	52	24	an	an	DET
fcis-6362	52	25	emotional	emotional	ADJ
fcis-6362	52	26	word	word	NOUN
fcis-6362	52	27	.	.	PUNCT
fcis-6362	53	1	alternatively	alternatively	ADV
fcis-6362	53	2	,	,	PUNCT
fcis-6362	53	3	if	if	SCONJ
fcis-6362	53	4	we	we	PRON
fcis-6362	53	5	choose	choose	VERB
fcis-6362	53	6	to	to	PART
fcis-6362	53	7	prompt	prompt	VERB
fcis-6362	53	8	the	the	DET
fcis-6362	53	9	lm	lm	NOUN
fcis-6362	53	10	with	with	ADP
fcis-6362	53	11	a	a	DET
fcis-6362	53	12	sentence	sentence	NOUN
fcis-6362	53	13	like	like	ADP
fcis-6362	53	14	"	"	PUNCT
fcis-6362	53	15	english	english	NOUN
fcis-6362	53	16	:	:	PUNCT
fcis-6362	53	17	i	i	PRON
fcis-6362	53	18	missed	miss	VERB
fcis-6362	53	19	the	the	DET
fcis-6362	53	20	bus	bus	NOUN
fcis-6362	53	21	today	today	NOUN
fcis-6362	53	22	.	.	PUNCT
fcis-6362	54	1	chinese	chinese	ADJ
fcis-6362	54	2	:	:	PUNCT
fcis-6362	55	1	_	_	PUNCT
fcis-6362	55	2	_	_	PUNCT
fcis-6362	55	3	"	"	PUNCT
fcis-6362	55	4	,	,	PUNCT
fcis-6362	55	5	we	we	PRON
fcis-6362	55	6	can	can	AUX
fcis-6362	55	7	evaluate	evaluate	VERB
fcis-6362	55	8	its	its	PRON
fcis-6362	55	9	ability	ability	NOUN
fcis-6362	55	10	to	to	PART
fcis-6362	55	11	perform	perform	VERB
fcis-6362	55	12	machine	machine	NOUN
fcis-6362	55	13	translation	translation	NOUN
fcis-6362	55	14	.	.	PUNCT
fcis-6362	56	1	due	due	ADP
fcis-6362	56	2	to	to	ADP
fcis-6362	56	3	the	the	DET
fcis-6362	56	4	fact	fact	NOUN
fcis-6362	56	5	that	that	SCONJ
fcis-6362	56	6	prompt	prompt	ADJ
fcis-6362	56	7	learning	learning	NOUN
fcis-6362	56	8	is	be	AUX
fcis-6362	56	9	closer	close	ADJ
fcis-6362	56	10	to	to	ADP
fcis-6362	56	11	the	the	DET
fcis-6362	56	12	pretraining	pretraine	VERB
fcis-6362	56	13	task	task	NOUN
fcis-6362	56	14	of	of	ADP
fcis-6362	56	15	the	the	DET
fcis-6362	56	16	language	language	NOUN
fcis-6362	56	17	model	model	NOUN
fcis-6362	56	18	,	,	PUNCT
fcis-6362	56	19	it	it	PRON
fcis-6362	56	20	has	have	AUX
fcis-6362	56	21	shown	show	VERB
fcis-6362	56	22	great	great	ADJ
fcis-6362	56	23	competitiveness	competitiveness	NOUN
fcis-6362	56	24	in	in	ADP
fcis-6362	56	25	zero	zero	NUM
fcis-6362	56	26	-	-	PUNCT
fcis-6362	56	27	shot	shot	NOUN
fcis-6362	56	28	learning	learning	NOUN
fcis-6362	56	29	and	and	CCONJ
fcis-6362	56	30	few	few	ADJ
fcis-6362	56	31	-	-	PUNCT
fcis-6362	56	32	shot	shot	NOUN
fcis-6362	56	33	learning	learn	VERB
fcis-6362	56	34	domains	domain	NOUN
fcis-6362	56	35	.	.	PUNCT
fcis-6362	57	1	to	to	PART
fcis-6362	57	2	be	be	AUX
fcis-6362	57	3	able	able	ADJ
fcis-6362	57	4	to	to	PART
fcis-6362	57	5	stimulate	stimulate	VERB
fcis-6362	57	6	the	the	DET
fcis-6362	57	7	language	language	NOUN
fcis-6362	57	8	ability	ability	NOUN
fcis-6362	57	9	acquired	acquire	VERB
fcis-6362	57	10	by	by	ADP
fcis-6362	57	11	the	the	DET
fcis-6362	57	12	model	model	NOUN
fcis-6362	57	13	during	during	ADP
fcis-6362	57	14	the	the	DET
fcis-6362	57	15	pre	pre	ADJ
fcis-6362	57	16	-	-	ADJ
fcis-6362	57	17	training	training	ADJ
fcis-6362	57	18	phase	phase	NOUN
fcis-6362	57	19	,	,	PUNCT
fcis-6362	57	20	the	the	DET
fcis-6362	57	21	selection	selection	NOUN
fcis-6362	57	22	of	of	ADP
fcis-6362	57	23	prompt	prompt	ADJ
fcis-6362	57	24	templates	template	NOUN
fcis-6362	57	25	is	be	AUX
fcis-6362	57	26	particularly	particularly	ADV
fcis-6362	57	27	important	important	ADJ
fcis-6362	57	28	.	.	PUNCT
fcis-6362	58	1	the	the	DET
fcis-6362	58	2	prompt	prompt	NOUN
fcis-6362	58	3	can	can	AUX
fcis-6362	58	4	be	be	AUX
fcis-6362	58	5	divided	divide	VERB
fcis-6362	58	6	into	into	ADP
fcis-6362	58	7	two	two	NUM
fcis-6362	58	8	categories	category	NOUN
fcis-6362	58	9	,	,	PUNCT
fcis-6362	58	10	hard	hard	ADJ
fcis-6362	58	11	prompts	prompt	NOUN
fcis-6362	58	12	(	(	PUNCT
fcis-6362	58	13	discrete	discrete	ADJ
fcis-6362	58	14	prompts	prompt	NOUN
fcis-6362	58	15	)	)	PUNCT
fcis-6362	58	16	and	and	CCONJ
fcis-6362	58	17	soft	soft	ADJ
fcis-6362	58	18	prompts	prompt	NOUN
fcis-6362	58	19	(	(	PUNCT
fcis-6362	58	20	continuous	continuous	ADJ
fcis-6362	58	21	prompts	prompt	NOUN
fcis-6362	58	22	)	)	PUNCT
fcis-6362	58	23	.	.	PUNCT
fcis-6362	59	1	hard	hard	ADJ
fcis-6362	59	2	prompts	prompt	NOUN
fcis-6362	59	3	refer	refer	VERB
fcis-6362	59	4	to	to	ADP
fcis-6362	59	5	prompts	prompt	NOUN
fcis-6362	59	6	that	that	PRON
fcis-6362	59	7	are	be	AUX
fcis-6362	59	8	manually	manually	ADV
fcis-6362	59	9	designed	design	VERB
fcis-6362	59	10	,	,	PUNCT
fcis-6362	59	11	that	that	ADV
fcis-6362	59	12	is	is	ADV
fcis-6362	59	13	,	,	PUNCT
fcis-6362	59	14	templates	template	NOUN
fcis-6362	59	15	designed	design	VERB
fcis-6362	59	16	by	by	ADP
fcis-6362	59	17	humans	human	NOUN
fcis-6362	59	18	.	.	PUNCT
fcis-6362	60	1	manual	manual	ADJ
fcis-6362	60	2	design	design	NOUN
fcis-6362	60	3	is	be	AUX
fcis-6362	60	4	generally	generally	ADV
fcis-6362	60	5	based	base	VERB
fcis-6362	60	6	on	on	ADP
fcis-6362	60	7	human	human	ADJ
fcis-6362	60	8	natural	natural	ADJ
fcis-6362	60	9	language	language	NOUN
fcis-6362	60	10	knowledge	knowledge	NOUN
fcis-6362	60	11	,	,	PUNCT
fcis-6362	60	12	striving	strive	VERB
fcis-6362	60	13	to	to	PART
fcis-6362	60	14	obtain	obtain	VERB
fcis-6362	60	15	semantically	semantically	ADV
fcis-6362	60	16	fluent	fluent	ADJ
fcis-6362	60	17	and	and	CCONJ
fcis-6362	60	18	efficient	efficient	ADJ
fcis-6362	60	19	templates	template	NOUN
fcis-6362	60	20	.	.	PUNCT
fcis-6362	61	1	in	in	ADP
fcis-6362	61	2	2020	2020	NUM
fcis-6362	61	3	,	,	PUNCT
fcis-6362	61	4	soft	soft	ADJ
fcis-6362	61	5	prompts	prompt	NOUN
fcis-6362	61	6	were	be	AUX
fcis-6362	61	7	proposed	propose	VERB
fcis-6362	61	8	.	.	PUNCT
fcis-6362	62	1	soft	soft	ADJ
fcis-6362	62	2	prompts	prompt	NOUN
fcis-6362	62	3	are	be	AUX
fcis-6362	62	4	exactly	exactly	ADV
fcis-6362	62	5	the	the	DET
fcis-6362	62	6	opposite	opposite	NOUN
fcis-6362	62	7	of	of	ADP
fcis-6362	62	8	hard	hard	ADJ
fcis-6362	62	9	prompts	prompt	NOUN
fcis-6362	62	10	.	.	PUNCT
fcis-6362	63	1	they	they	PRON
fcis-6362	63	2	learn	learn	VERB
fcis-6362	63	3	the	the	DET
fcis-6362	63	4	generation	generation	NOUN
fcis-6362	63	5	of	of	ADP
fcis-6362	63	6	prompts	prompt	NOUN
fcis-6362	63	7	as	as	ADP
fcis-6362	63	8	a	a	DET
fcis-6362	63	9	task	task	NOUN
fcis-6362	63	10	,	,	PUNCT
fcis-6362	63	11	which	which	PRON
fcis-6362	63	12	is	be	AUX
fcis-6362	63	13	equivalent	equivalent	ADJ
fcis-6362	63	14	to	to	ADP
fcis-6362	63	15	changing	change	VERB
fcis-6362	63	16	the	the	DET
fcis-6362	63	17	generation	generation	NOUN
fcis-6362	63	18	of	of	ADP
fcis-6362	63	19	prompts	prompt	NOUN
fcis-6362	63	20	from	from	ADP
fcis-6362	63	21	human	human	ADJ
fcis-6362	63	22	(	(	PUNCT
fcis-6362	63	23	discrete	discrete	NOUN
fcis-6362	63	24	)	)	PUNCT
fcis-6362	63	25	to	to	ADP
fcis-6362	63	26	machine	machine	NOUN
fcis-6362	63	27	learning	learning	NOUN
fcis-6362	63	28	(	(	PUNCT
fcis-6362	63	29	continuous	continuous	ADJ
fcis-6362	63	30	)	)	PUNCT
fcis-6362	63	31	.	.	PUNCT
fcis-6362	64	1	hard	hard	ADJ
fcis-6362	64	2	prompts	prompt	NOUN
fcis-6362	64	3	and	and	CCONJ
fcis-6362	64	4	soft	soft	ADJ
fcis-6362	64	5	prompts	prompt	NOUN
fcis-6362	64	6	each	each	PRON
fcis-6362	64	7	have	have	VERB
fcis-6362	64	8	their	their	PRON
fcis-6362	64	9	advantages	advantage	NOUN
fcis-6362	64	10	and	and	CCONJ
fcis-6362	64	11	disadvantages	disadvantage	NOUN
fcis-6362	64	12	.	.	PUNCT
fcis-6362	65	1	the	the	DET
fcis-6362	65	2	advantage	advantage	NOUN
fcis-6362	65	3	of	of	ADP
fcis-6362	65	4	hard	hard	ADJ
fcis-6362	65	5	prompts	prompt	NOUN
fcis-6362	65	6	is	be	AUX
fcis-6362	65	7	that	that	SCONJ
fcis-6362	65	8	they	they	PRON
fcis-6362	65	9	have	have	VERB
fcis-6362	65	10	good	good	ADJ
fcis-6362	65	11	interpretability	interpretability	NOUN
fcis-6362	65	12	and	and	CCONJ
fcis-6362	65	13	can	can	AUX
fcis-6362	65	14	be	be	AUX
fcis-6362	65	15	presented	present	VERB
fcis-6362	65	16	in	in	ADP
fcis-6362	65	17	a	a	DET
fcis-6362	65	18	form	form	NOUN
fcis-6362	65	19	that	that	PRON
fcis-6362	65	20	humans	human	NOUN
fcis-6362	65	21	can	can	AUX
fcis-6362	65	22	read	read	VERB
fcis-6362	65	23	.	.	PUNCT
fcis-6362	66	1	the	the	DET
fcis-6362	66	2	disadvantage	disadvantage	NOUN
fcis-6362	66	3	,	,	PUNCT
fcis-6362	66	4	however	however	ADV
fcis-6362	66	5	,	,	PUNCT
fcis-6362	66	6	is	be	AUX
fcis-6362	66	7	that	that	SCONJ
fcis-6362	66	8	what	what	PRON
fcis-6362	66	9	humans	human	NOUN
fcis-6362	66	10	consider	consider	VERB
fcis-6362	66	11	to	to	PART
fcis-6362	66	12	be	be	AUX
fcis-6362	66	13	good	good	ADJ
fcis-6362	66	14	hard	hard	ADJ
fcis-6362	66	15	prompts	prompt	NOUN
fcis-6362	66	16	may	may	AUX
fcis-6362	66	17	not	not	PART
fcis-6362	66	18	necessarily	necessarily	ADV
fcis-6362	66	19	be	be	AUX
fcis-6362	66	20	good	good	ADJ
fcis-6362	66	21	hard	hard	ADJ
fcis-6362	66	22	prompts	prompt	NOUN
fcis-6362	66	23	for	for	ADP
fcis-6362	66	24	a	a	DET
fcis-6362	66	25	language	language	NOUN
fcis-6362	66	26	model	model	NOUN
fcis-6362	66	27	.	.	PUNCT
fcis-6362	67	1	this	this	DET
fcis-6362	67	2	property	property	NOUN
fcis-6362	67	3	is	be	AUX
fcis-6362	67	4	known	know	VERB
fcis-6362	67	5	as	as	ADP
fcis-6362	67	6	the	the	DET
fcis-6362	67	7	sub	sub	NOUN
fcis-6362	67	8	-	-	NOUN
fcis-6362	67	9	optimality	optimality	NOUN
fcis-6362	67	10	of	of	ADP
fcis-6362	67	11	hard	hard	ADJ
fcis-6362	67	12	prompts	prompt	NOUN
fcis-6362	67	13	,	,	PUNCT
fcis-6362	67	14	where	where	SCONJ
fcis-6362	67	15	the	the	DET
fcis-6362	67	16	selection	selection	NOUN
fcis-6362	67	17	of	of	ADP
fcis-6362	67	18	hard	hard	ADJ
fcis-6362	67	19	prompts	prompt	NOUN
fcis-6362	67	20	can	can	AUX
fcis-6362	67	21	have	have	VERB
fcis-6362	67	22	a	a	DET
fcis-6362	67	23	significant	significant	ADJ
fcis-6362	67	24	impact	impact	NOUN
fcis-6362	67	25	on	on	ADP
fcis-6362	67	26	the	the	DET
fcis-6362	67	27	performance	performance	NOUN
fcis-6362	67	28	and	and	CCONJ
fcis-6362	67	29	stability	stability	NOUN
fcis-6362	67	30	of	of	ADP
fcis-6362	67	31	pre	pre	ADJ
fcis-6362	67	32	-	-	ADJ
fcis-6362	67	33	trained	train	VERB
fcis-6362	67	34	models	model	NOUN
fcis-6362	67	35	.	.	PUNCT
fcis-6362	68	1	on	on	ADP
fcis-6362	68	2	the	the	DET
fcis-6362	68	3	other	other	ADJ
fcis-6362	68	4	hand	hand	NOUN
fcis-6362	68	5	,	,	PUNCT
fcis-6362	68	6	soft	soft	ADJ
fcis-6362	68	7	prompts	prompt	NOUN
fcis-6362	68	8	are	be	AUX
fcis-6362	68	9	the	the	DET
fcis-6362	68	10	opposite	opposite	NOUN
fcis-6362	68	11	.	.	PUNCT
fcis-6362	69	1	they	they	PRON
fcis-6362	69	2	are	be	AUX
fcis-6362	69	3	learned	learn	VERB
fcis-6362	69	4	by	by	ADP
fcis-6362	69	5	the	the	DET
fcis-6362	69	6	model	model	NOUN
fcis-6362	69	7	and	and	CCONJ
fcis-6362	69	8	are	be	AUX
fcis-6362	69	9	more	more	ADV
fcis-6362	69	10	stable	stable	ADJ
fcis-6362	69	11	than	than	ADP
fcis-6362	69	12	hard	hard	ADJ
fcis-6362	69	13	prompts	prompt	NOUN
fcis-6362	69	14	,	,	PUNCT
fcis-6362	69	15	but	but	CCONJ
fcis-6362	69	16	lack	lack	VERB
fcis-6362	69	17	interpretability	interpretability	NOUN
fcis-6362	69	18	,	,	PUNCT
fcis-6362	69	19	making	make	VERB
fcis-6362	69	20	them	they	PRON
fcis-6362	69	21	difficult	difficult	ADJ
fcis-6362	69	22	to	to	PART
fcis-6362	69	23	apply	apply	VERB
fcis-6362	69	24	in	in	ADP
fcis-6362	69	25	tasks	task	NOUN
fcis-6362	69	26	that	that	PRON
fcis-6362	69	27	require	require	VERB
fcis-6362	69	28	strong	strong	ADJ
fcis-6362	69	29	interpretability	interpretability	NOUN
fcis-6362	69	30	.	.	PUNCT
fcis-6362	70	1	in	in	ADP
fcis-6362	70	2	our	our	PRON
fcis-6362	70	3	work	work	NOUN
fcis-6362	70	4	,	,	PUNCT
fcis-6362	70	5	we	we	PRON
fcis-6362	70	6	propose	propose	VERB
fcis-6362	70	7	a	a	DET
fcis-6362	70	8	learning	learning	NOUN
fcis-6362	70	9	strategy	strategy	NOUN
fcis-6362	70	10	that	that	PRON
fcis-6362	70	11	is	be	AUX
fcis-6362	70	12	conjugate	conjugate	ADJ
fcis-6362	70	13	to	to	ADP
fcis-6362	70	14	prompt	prompt	ADJ
fcis-6362	70	15	learning	learning	NOUN
fcis-6362	70	16	for	for	ADP
fcis-6362	70	17	few	few	ADJ
fcis-6362	70	18	shot	shot	NOUN
fcis-6362	70	19	tasks	task	NOUN
fcis-6362	70	20	.	.	PUNCT
fcis-6362	71	1	in	in	ADP
fcis-6362	71	2	prompt	prompt	ADJ
fcis-6362	71	3	learning	learning	NOUN
fcis-6362	71	4	,	,	PUNCT
fcis-6362	71	5	the	the	DET
fcis-6362	71	6	input	input	NOUN
fcis-6362	71	7	text	text	NOUN
fcis-6362	71	8	is	be	AUX
fcis-6362	71	9	fixed	fix	VERB
fcis-6362	71	10	and	and	CCONJ
fcis-6362	71	11	the	the	DET
fcis-6362	71	12	model	model	NOUN
fcis-6362	71	13	is	be	AUX
fcis-6362	71	14	required	require	VERB
fcis-6362	71	15	to	to	PART
fcis-6362	71	16	fill	fill	VERB
fcis-6362	71	17	in	in	ADP
fcis-6362	71	18	the	the	DET
fcis-6362	71	19	target	target	NOUN
fcis-6362	71	20	word	word	NOUN
fcis-6362	71	21	.	.	PUNCT
fcis-6362	72	1	we	we	PRON
fcis-6362	72	2	reversed	reverse	VERB
fcis-6362	72	3	this	this	DET
fcis-6362	72	4	task	task	NOUN
fcis-6362	72	5	by	by	ADP
fcis-6362	72	6	fixing	fix	VERB
fcis-6362	72	7	the	the	DET
fcis-6362	72	8	target	target	NOUN
fcis-6362	72	9	word	word	NOUN
fcis-6362	72	10	and	and	CCONJ
fcis-6362	72	11	requiring	require	VERB
fcis-6362	72	12	the	the	DET
fcis-6362	72	13	model	model	NOUN
fcis-6362	72	14	to	to	PART
fcis-6362	72	15	fill	fill	VERB
fcis-6362	72	16	in	in	ADP
fcis-6362	72	17	the	the	DET
fcis-6362	72	18	input	input	NOUN
fcis-6362	72	19	text	text	NOUN
fcis-6362	72	20	.	.	PUNCT
fcis-6362	73	1	this	this	PRON
fcis-6362	73	2	is	be	AUX
fcis-6362	73	3	based	base	VERB
fcis-6362	73	4	on	on	ADP
fcis-6362	73	5	the	the	DET
fcis-6362	73	6	same	same	ADJ
fcis-6362	73	7	assumption	assumption	NOUN
fcis-6362	73	8	as	as	ADP
fcis-6362	73	9	prompt	prompt	ADJ
fcis-6362	73	10	learning	learning	NOUN
fcis-6362	73	11	,	,	PUNCT
fcis-6362	73	12	that	that	SCONJ
fcis-6362	73	13	the	the	DET
fcis-6362	73	14	language	language	NOUN
fcis-6362	73	15	ability	ability	NOUN
fcis-6362	73	16	learned	learn	VERB
fcis-6362	73	17	by	by	ADP
fcis-6362	73	18	the	the	DET
fcis-6362	73	19	language	language	NOUN
fcis-6362	73	20	model	model	NOUN
fcis-6362	73	21	can	can	AUX
fcis-6362	73	22	not	not	PART
fcis-6362	73	23	only	only	ADV
fcis-6362	73	24	fill	fill	VERB
fcis-6362	73	25	in	in	ADP
fcis-6362	73	26	the	the	DET
fcis-6362	73	27	target	target	NOUN
fcis-6362	73	28	word	word	NOUN
fcis-6362	73	29	,	,	PUNCT
fcis-6362	73	30	but	but	CCONJ
fcis-6362	73	31	also	also	ADV
fcis-6362	73	32	deduce	deduce	VERB
fcis-6362	73	33	the	the	DET
fcis-6362	73	34	missing	miss	VERB
fcis-6362	73	35	content	content	NOUN
fcis-6362	73	36	in	in	ADP
fcis-6362	73	37	the	the	DET
fcis-6362	73	38	original	original	ADJ
fcis-6362	73	39	text	text	NOUN
fcis-6362	73	40	from	from	ADP
fcis-6362	73	41	the	the	DET
fcis-6362	73	42	target	target	NOUN
fcis-6362	73	43	word	word	NOUN
fcis-6362	73	44	.	.	PUNCT
fcis-6362	74	1	the	the	DET
fcis-6362	74	2	results	result	NOUN
fcis-6362	74	3	show	show	VERB
fcis-6362	74	4	that	that	SCONJ
fcis-6362	74	5	on	on	ADP
fcis-6362	74	6	multiple	multiple	ADJ
fcis-6362	74	7	public	public	ADJ
fcis-6362	74	8	datasets	dataset	NOUN
fcis-6362	74	9	,	,	PUNCT
fcis-6362	74	10	whether	whether	SCONJ
fcis-6362	74	11	our	our	PRON
fcis-6362	74	12	method	method	NOUN
fcis-6362	74	13	is	be	AUX
fcis-6362	74	14	applied	apply	VERB
fcis-6362	74	15	alone	alone	ADV
fcis-6362	74	16	or	or	CCONJ
fcis-6362	74	17	trained	train	VERB
fcis-6362	74	18	jointly	jointly	ADV
fcis-6362	74	19	with	with	ADP
fcis-6362	74	20	the	the	DET
fcis-6362	74	21	original	original	ADJ
fcis-6362	74	22	prompt	prompt	ADJ
fcis-6362	74	23	learning	learning	NOUN
fcis-6362	74	24	,	,	PUNCT
fcis-6362	74	25	it	it	PRON
fcis-6362	74	26	can	can	AUX
fcis-6362	74	27	effectively	effectively	ADV
fcis-6362	74	28	improve	improve	VERB
fcis-6362	74	29	the	the	DET
fcis-6362	74	30	model	model	NOUN
fcis-6362	74	31	's	's	PART
fcis-6362	74	32	ability	ability	NOUN
fcis-6362	74	33	in	in	ADP
fcis-6362	74	34	fewshot	fewshot	ADJ
fcis-6362	74	35	tasks	task	NOUN
fcis-6362	74	36	.	.	PUNCT
fcis-6362	75	1	2	2	X
fcis-6362	75	2	.	.	X
fcis-6362	75	3	related	relate	VERB
fcis-6362	75	4	work	work	NOUN
fcis-6362	75	5	the	the	DET
fcis-6362	75	6	work	work	NOUN
fcis-6362	75	7	on	on	ADP
fcis-6362	75	8	prompt	prompt	NOUN
fcis-6362	75	9	emerged	emerge	VERB
fcis-6362	75	10	around	around	ADP
fcis-6362	75	11	2019	2019	NUM
fcis-6362	75	12	.	.	PUNCT
fcis-6362	76	1	many	many	ADJ
fcis-6362	76	2	researchers	researcher	NOUN
fcis-6362	76	3	began	begin	VERB
fcis-6362	76	4	to	to	PART
fcis-6362	76	5	focus	focus	VERB
fcis-6362	76	6	on	on	ADP
fcis-6362	76	7	extracting	extract	VERB
fcis-6362	76	8	knowledge	knowledge	NOUN
fcis-6362	76	9	from	from	ADP
fcis-6362	76	10	large	large	ADJ
fcis-6362	76	11	pre	pre	ADJ
fcis-6362	76	12	-	-	ADJ
fcis-6362	76	13	trained	train	VERB
fcis-6362	76	14	models	model	NOUN
fcis-6362	76	15	and	and	CCONJ
fcis-6362	76	16	applying	apply	VERB
fcis-6362	76	17	it	it	PRON
fcis-6362	76	18	to	to	ADP
fcis-6362	76	19	different	different	ADJ
fcis-6362	76	20	downstream	downstream	ADJ
fcis-6362	76	21	tasks	task	NOUN
fcis-6362	76	22	.	.	PUNCT
fcis-6362	77	1	lewis	lewis	PROPN
fcis-6362	77	2	et	et	PROPN
fcis-6362	77	3	al	al	PROPN
fcis-6362	78	1	[	[	X
fcis-6362	78	2	8	8	NUM
fcis-6362	78	3	]	]	PUNCT
fcis-6362	78	4	.	.	PUNCT
fcis-6362	79	1	introduce	introduce	VERB
fcis-6362	79	2	rag	rag	NOUN
fcis-6362	79	3	models	model	NOUN
fcis-6362	79	4	where	where	SCONJ
fcis-6362	79	5	the	the	DET
fcis-6362	79	6	parametric	parametric	ADJ
fcis-6362	79	7	memory	memory	NOUN
fcis-6362	79	8	is	be	AUX
fcis-6362	79	9	a	a	DET
fcis-6362	79	10	pre	pre	ADJ
fcis-6362	79	11	-	-	ADJ
fcis-6362	79	12	trained	train	VERB
fcis-6362	79	13	seq2seq	seq2seq	NOUN
fcis-6362	79	14	model	model	NOUN
fcis-6362	79	15	and	and	CCONJ
fcis-6362	79	16	the	the	DET
fcis-6362	79	17	non	non	ADJ
fcis-6362	79	18	-	-	ADJ
fcis-6362	79	19	parametric	parametric	ADJ
fcis-6362	79	20	memory	memory	NOUN
fcis-6362	79	21	is	be	AUX
fcis-6362	79	22	a	a	DET
fcis-6362	79	23	dense	dense	ADJ
fcis-6362	79	24	vector	vector	NOUN
fcis-6362	79	25	index	index	NOUN
fcis-6362	79	26	of	of	ADP
fcis-6362	79	27	wikipedia	wikipedia	PROPN
fcis-6362	79	28	,	,	PUNCT
fcis-6362	79	29	accessed	access	VERB
fcis-6362	79	30	with	with	ADP
fcis-6362	79	31	a	a	DET
fcis-6362	79	32	pre	pre	ADJ
fcis-6362	79	33	-	-	ADJ
fcis-6362	79	34	trained	train	VERB
fcis-6362	79	35	neural	neural	ADJ
fcis-6362	79	36	retriever	retriever	NOUN
fcis-6362	79	37	.	.	PUNCT
fcis-6362	80	1	the	the	DET
fcis-6362	80	2	result	result	NOUN
fcis-6362	80	3	shows	show	VERB
fcis-6362	80	4	that	that	SCONJ
fcis-6362	80	5	rag	rag	NOUN
fcis-6362	80	6	models	model	NOUN
fcis-6362	80	7	generate	generate	VERB
fcis-6362	80	8	more	more	ADV
fcis-6362	80	9	specific	specific	ADJ
fcis-6362	80	10	,	,	PUNCT
fcis-6362	80	11	diverse	diverse	ADJ
fcis-6362	80	12	and	and	CCONJ
fcis-6362	80	13	factual	factual	ADJ
fcis-6362	80	14	language	language	NOUN
fcis-6362	80	15	than	than	ADP
fcis-6362	80	16	a	a	DET
fcis-6362	80	17	state	state	NOUN
fcis-6362	80	18	-	-	PUNCT
fcis-6362	80	19	of	of	ADP
fcis-6362	80	20	-	-	PUNCT
fcis-6362	80	21	the	the	DET
fcis-6362	80	22	-	-	PUNCT
fcis-6362	80	23	art	art	NOUN
fcis-6362	80	24	parametric	parametric	NOUN
fcis-6362	80	25	-	-	PUNCT
fcis-6362	80	26	only	only	ADV
fcis-6362	80	27	seq2seq	seq2seq	NOUN
fcis-6362	80	28	baseline	baseline	NOUN
fcis-6362	80	29	.	.	PUNCT
fcis-6362	81	1	jiang	jiang	PROPN
fcis-6362	81	2	et	et	PROPN
fcis-6362	81	3	al[9	al[9	VERB
fcis-6362	81	4	]	]	PUNCT
fcis-6362	81	5	.	.	PUNCT
fcis-6362	82	1	propose	propose	VERB
fcis-6362	82	2	methods	method	NOUN
fcis-6362	82	3	to	to	PART
fcis-6362	82	4	improve	improve	VERB
fcis-6362	82	5	the	the	DET
fcis-6362	82	6	accuracy	accuracy	NOUN
fcis-6362	82	7	of	of	ADP
fcis-6362	82	8	estimating	estimate	VERB
fcis-6362	82	9	the	the	DET
fcis-6362	82	10	knowledge	knowledge	NOUN
fcis-6362	82	11	contained	contain	VERB
fcis-6362	82	12	in	in	ADP
fcis-6362	82	13	lms	lm	NOUN
fcis-6362	82	14	by	by	ADP
fcis-6362	82	15	automatically	automatically	ADV
fcis-6362	82	16	generating	generate	VERB
fcis-6362	82	17	better	well	ADJ
fcis-6362	82	18	prompts	prompt	NOUN
fcis-6362	82	19	for	for	ADP
fcis-6362	82	20	querying	query	VERB
fcis-6362	82	21	.	.	PUNCT
fcis-6362	83	1	our	our	PRON
fcis-6362	83	2	methods	method	NOUN
fcis-6362	83	3	include	include	VERB
fcis-6362	83	4	mining	mining	NOUN
fcis-6362	83	5	-	-	PUNCT
fcis-6362	83	6	based	base	VERB
fcis-6362	83	7	and	and	CCONJ
fcis-6362	83	8	paraphrasing	paraphrasing	NOUN
fcis-6362	83	9	-	-	PUNCT
fcis-6362	83	10	based	base	VERB
fcis-6362	83	11	approaches	approach	NOUN
fcis-6362	83	12	to	to	PART
fcis-6362	83	13	generate	generate	VERB
fcis-6362	83	14	high	high	ADJ
fcis-6362	83	15	-	-	PUNCT
fcis-6362	83	16	quality	quality	NOUN
fcis-6362	83	17	and	and	CCONJ
fcis-6362	83	18	diverse	diverse	ADJ
fcis-6362	83	19	prompts	prompt	NOUN
fcis-6362	83	20	,	,	PUNCT
fcis-6362	83	21	and	and	CCONJ
fcis-6362	83	22	ensemble	ensemble	ADJ
fcis-6362	83	23	methods	method	NOUN
fcis-6362	83	24	to	to	PART
fcis-6362	83	25	combine	combine	VERB
fcis-6362	83	26	answers	answer	NOUN
fcis-6362	83	27	from	from	ADP
fcis-6362	83	28	multiple	multiple	ADJ
fcis-6362	83	29	prompts	prompt	NOUN
fcis-6362	83	30	.	.	PUNCT
fcis-6362	84	1	they	they	PRON
fcis-6362	84	2	conducted	conduct	VERB
fcis-6362	84	3	extensive	extensive	ADJ
fcis-6362	84	4	experiments	experiment	NOUN
fcis-6362	84	5	on	on	ADP
fcis-6362	84	6	the	the	DET
fcis-6362	84	7	lama	lama	PROPN
fcis-6362	84	8	benchmark	benchmark	NOUN
fcis-6362	84	9	,	,	PUNCT
fcis-6362	84	10	which	which	PRON
fcis-6362	84	11	extracts	extract	VERB
fcis-6362	84	12	relational	relational	ADJ
fcis-6362	84	13	knowledge	knowledge	NOUN
fcis-6362	84	14	from	from	ADP
fcis-6362	84	15	lms	lm	NOUN
fcis-6362	84	16	,	,	PUNCT
fcis-6362	84	17	and	and	CCONJ
fcis-6362	84	18	found	find	VERB
fcis-6362	84	19	that	that	SCONJ
fcis-6362	84	20	methods	method	NOUN
fcis-6362	84	21	improved	improved	ADJ
fcis-6362	84	22	accuracy	accuracy	NOUN
fcis-6362	84	23	from	from	ADP
fcis-6362	84	24	31.1	31.1	NUM
fcis-6362	84	25	%	%	NOUN
fcis-6362	84	26	to	to	ADP
fcis-6362	84	27	39.6	39.6	NUM
fcis-6362	84	28	%	%	NOUN
fcis-6362	84	29	.	.	PUNCT
fcis-6362	85	1	radford	radford	PROPN
fcis-6362	85	2	et	et	PROPN
fcis-6362	85	3	al	al	PROPN
fcis-6362	86	1	[	[	X
fcis-6362	86	2	10	10	NUM
fcis-6362	86	3	]	]	PUNCT
fcis-6362	86	4	.	.	PUNCT
fcis-6362	87	1	show	show	VERB
fcis-6362	87	2	that	that	SCONJ
fcis-6362	87	3	substantial	substantial	ADJ
fcis-6362	87	4	improvements	improvement	NOUN
fcis-6362	87	5	in	in	ADP
fcis-6362	87	6	performance	performance	NOUN
fcis-6362	87	7	on	on	ADP
fcis-6362	87	8	various	various	ADJ
fcis-6362	87	9	tasks	task	NOUN
fcis-6362	87	10	can	can	AUX
fcis-6362	87	11	be	be	AUX
fcis-6362	87	12	achieved	achieve	VERB
fcis-6362	87	13	by	by	ADP
fcis-6362	87	14	employing	employ	VERB
fcis-6362	87	15	a	a	DET
fcis-6362	87	16	two	two	NUM
fcis-6362	87	17	-	-	PUNCT
fcis-6362	87	18	stage	stage	NOUN
fcis-6362	87	19	approach	approach	NOUN
fcis-6362	87	20	:	:	PUNCT
fcis-6362	87	21	generative	generative	ADJ
fcis-6362	87	22	pretraining	pretraine	VERB
fcis-6362	87	23	of	of	ADP
fcis-6362	87	24	a	a	DET
fcis-6362	87	25	language	language	NOUN
fcis-6362	87	26	model	model	NOUN
fcis-6362	87	27	using	use	VERB
fcis-6362	87	28	a	a	DET
fcis-6362	87	29	diverse	diverse	ADJ
fcis-6362	87	30	corpus	corpus	NOUN
fcis-6362	87	31	of	of	ADP
fcis-6362	87	32	unlabeled	unlabeled	ADJ
fcis-6362	87	33	text	text	NOUN
fcis-6362	87	34	,	,	PUNCT
fcis-6362	87	35	followed	follow	VERB
fcis-6362	87	36	by	by	ADP
fcis-6362	87	37	discriminative	discriminative	NOUN
fcis-6362	87	38	fine	fine	ADV
fcis-6362	87	39	-	-	PUNCT
fcis-6362	87	40	tuning	tuning	NOUN
fcis-6362	87	41	on	on	ADP
fcis-6362	87	42	each	each	DET
fcis-6362	87	43	specific	specific	ADJ
fcis-6362	87	44	task	task	NOUN
fcis-6362	87	45	.	.	PUNCT
fcis-6362	88	1	by	by	ADP
fcis-6362	88	2	tailoring	tailor	VERB
fcis-6362	88	3	the	the	DET
fcis-6362	88	4	architecture	architecture	NOUN
fcis-6362	88	5	of	of	ADP
fcis-6362	88	6	the	the	DET
fcis-6362	88	7	model	model	NOUN
fcis-6362	88	8	to	to	ADP
fcis-6362	88	9	multiple	multiple	ADJ
fcis-6362	88	10	tasks	task	NOUN
fcis-6362	88	11	,	,	PUNCT
fcis-6362	88	12	their	their	PRON
fcis-6362	88	13	methods	method	NOUN
fcis-6362	88	14	were	be	AUX
fcis-6362	88	15	able	able	ADJ
fcis-6362	88	16	to	to	PART
fcis-6362	88	17	significantly	significantly	ADV
fcis-6362	88	18	surpass	surpass	VERB
fcis-6362	88	19	the	the	DET
fcis-6362	88	20	state	state	NOUN
fcis-6362	88	21	of	of	ADP
fcis-6362	88	22	the	the	DET
fcis-6362	88	23	art	art	NOUN
fcis-6362	88	24	in	in	ADP
fcis-6362	88	25	9	9	NUM
fcis-6362	88	26	out	out	ADP
fcis-6362	88	27	of	of	ADP
fcis-6362	88	28	the	the	DET
fcis-6362	88	29	12	12	NUM
fcis-6362	88	30	tasks	task	NOUN
fcis-6362	88	31	.	.	PUNCT
fcis-6362	89	1	once	once	ADV
fcis-6362	89	2	proposed	propose	VERB
fcis-6362	89	3	,	,	PUNCT
fcis-6362	89	4	prompt	prompt	ADJ
fcis-6362	89	5	learning	learning	NOUN
fcis-6362	89	6	became	become	VERB
fcis-6362	89	7	popular	popular	ADJ
fcis-6362	89	8	in	in	ADP
fcis-6362	89	9	the	the	DET
fcis-6362	89	10	zero	zero	NUM
fcis-6362	89	11	-	-	PUNCT
fcis-6362	89	12	shot	shot	NOUN
fcis-6362	89	13	and	and	CCONJ
fcis-6362	89	14	few	few	ADJ
fcis-6362	89	15	-	-	PUNCT
fcis-6362	89	16	shot	shot	NOUN
fcis-6362	89	17	learning	learn	VERB
fcis-6362	89	18	fields	field	NOUN
fcis-6362	89	19	.	.	PUNCT
fcis-6362	90	1	compared	compare	VERB
fcis-6362	90	2	to	to	ADP
fcis-6362	90	3	the	the	DET
fcis-6362	90	4	paradigm	paradigm	NOUN
fcis-6362	90	5	of	of	ADP
fcis-6362	90	6	"	"	PUNCT
fcis-6362	90	7	pre	pre	ADJ
fcis-6362	90	8	-	-	ADJ
fcis-6362	90	9	train	train	ADJ
fcis-6362	90	10	and	and	CCONJ
fcis-6362	90	11	fine	fine	ADJ
fcis-6362	90	12	-	-	PUNCT
fcis-6362	90	13	tune	tune	NOUN
fcis-6362	90	14	"	"	PUNCT
fcis-6362	90	15	which	which	PRON
fcis-6362	90	16	requires	require	VERB
fcis-6362	90	17	the	the	DET
fcis-6362	90	18	model	model	NOUN
fcis-6362	90	19	to	to	PART
fcis-6362	90	20	learn	learn	VERB
fcis-6362	90	21	the	the	DET
fcis-6362	90	22	specific	specific	ADJ
fcis-6362	90	23	features	feature	NOUN
fcis-6362	90	24	needed	need	VERB
fcis-6362	90	25	to	to	PART
fcis-6362	90	26	output	output	VERB
fcis-6362	90	27	specific	specific	ADJ
fcis-6362	90	28	tasks	task	NOUN
fcis-6362	90	29	on	on	ADP
fcis-6362	90	30	specific	specific	ADJ
fcis-6362	90	31	labels	label	NOUN
fcis-6362	90	32	,	,	PUNCT
fcis-6362	90	33	prompt	prompt	ADJ
fcis-6362	90	34	learning	learning	NOUN
fcis-6362	90	35	directly	directly	ADV
fcis-6362	90	36	utilizes	utilize	VERB
fcis-6362	90	37	the	the	DET
fcis-6362	90	38	language	language	NOUN
fcis-6362	90	39	ability	ability	NOUN
fcis-6362	90	40	inherent	inherent	ADJ
fcis-6362	90	41	in	in	ADP
fcis-6362	90	42	the	the	DET
fcis-6362	90	43	pretrained	pretraine	VERB
fcis-6362	90	44	model	model	NOUN
fcis-6362	90	45	.	.	PUNCT
fcis-6362	91	1	its	its	PRON
fcis-6362	91	2	usage	usage	NOUN
fcis-6362	91	3	is	be	AUX
fcis-6362	91	4	closer	close	ADJ
fcis-6362	91	5	to	to	ADP
fcis-6362	91	6	the	the	DET
fcis-6362	91	7	paradigm	paradigm	NOUN
fcis-6362	91	8	during	during	ADP
fcis-6362	91	9	model	model	NOUN
fcis-6362	91	10	pretraining	pretraining	NOUN
fcis-6362	91	11	,	,	PUNCT
fcis-6362	91	12	and	and	CCONJ
fcis-6362	91	13	therefore	therefore	ADV
fcis-6362	91	14	,	,	PUNCT
fcis-6362	91	15	it	it	PRON
fcis-6362	91	16	can	can	AUX
fcis-6362	91	17	quickly	quickly	ADV
fcis-6362	91	18	start	start	VERB
fcis-6362	91	19	downstream	downstream	ADJ
fcis-6362	91	20	tasks	task	NOUN
fcis-6362	91	21	.	.	PUNCT
fcis-6362	92	1	li	li	PROPN
fcis-6362	92	2	et	et	PROPN
fcis-6362	92	3	al	al	PROPN
fcis-6362	93	1	[	[	X
fcis-6362	93	2	11	11	NUM
fcis-6362	93	3	]	]	PUNCT
fcis-6362	93	4	.	.	PUNCT
fcis-6362	94	1	proposed	propose	VERB
fcis-6362	94	2	prefix	prefix	NOUN
fcis-6362	94	3	-	-	PUNCT
fcis-6362	94	4	tuning	tuning	NOUN
fcis-6362	94	5	,	,	PUNCT
fcis-6362	94	6	a	a	DET
fcis-6362	94	7	lightweight	lightweight	ADJ
fcis-6362	94	8	alternative	alternative	NOUN
fcis-6362	94	9	to	to	ADP
fcis-6362	94	10	finetuning	finetune	VERB
fcis-6362	94	11	for	for	ADP
fcis-6362	94	12	natural	natural	ADJ
fcis-6362	94	13	language	language	NOUN
fcis-6362	94	14	generation	generation	NOUN
fcis-6362	94	15	tasks	task	NOUN
fcis-6362	94	16	,	,	PUNCT
fcis-6362	94	17	which	which	PRON
fcis-6362	94	18	keeps	keep	VERB
fcis-6362	94	19	language	language	NOUN
fcis-6362	94	20	model	model	NOUN
fcis-6362	94	21	parameters	parameter	NOUN
fcis-6362	94	22	frozen	freeze	VERB
fcis-6362	94	23	,	,	PUNCT
fcis-6362	94	24	but	but	CCONJ
fcis-6362	94	25	optimizes	optimize	VERB
fcis-6362	94	26	a	a	DET
fcis-6362	94	27	small	small	ADJ
fcis-6362	94	28	continuous	continuous	ADJ
fcis-6362	94	29	task	task	NOUN
fcis-6362	94	30	-	-	PUNCT
fcis-6362	94	31	specific	specific	ADJ
fcis-6362	94	32	vector	vector	NOUN
fcis-6362	94	33	(	(	PUNCT
fcis-6362	94	34	called	call	VERB
fcis-6362	94	35	the	the	DET
fcis-6362	94	36	prefix	prefix	NOUN
fcis-6362	94	37	)	)	PUNCT
fcis-6362	94	38	.	.	PUNCT
fcis-6362	95	1	findings	finding	NOUN
fcis-6362	95	2	indicate	indicate	VERB
fcis-6362	95	3	that	that	DET
fcis-6362	95	4	prefix	prefix	NOUN
fcis-6362	95	5	-	-	PUNCT
fcis-6362	95	6	tuning	tuning	NOUN
fcis-6362	95	7	achieves	achieve	VERB
fcis-6362	95	8	comparable	comparable	ADJ
fcis-6362	95	9	performance	performance	NOUN
fcis-6362	95	10	to	to	ADP
fcis-6362	95	11	fine	fine	ADV
fcis-6362	95	12	-	-	PUNCT
fcis-6362	95	13	tuning	tuning	NOUN
fcis-6362	95	14	on	on	ADP
fcis-6362	95	15	the	the	DET
fcis-6362	95	16	full	full	ADJ
fcis-6362	95	17	dataset	dataset	NOUN
fcis-6362	95	18	by	by	ADP
fcis-6362	95	19	learning	learn	VERB
fcis-6362	95	20	only	only	ADV
fcis-6362	95	21	0.1	0.1	NUM
fcis-6362	95	22	%	%	NOUN
fcis-6362	95	23	of	of	ADP
fcis-6362	95	24	the	the	DET
fcis-6362	95	25	parameters	parameter	NOUN
fcis-6362	95	26	.	.	PUNCT
fcis-6362	96	1	in	in	ADP
fcis-6362	96	2	settings	setting	NOUN
fcis-6362	96	3	with	with	ADP
fcis-6362	96	4	limited	limited	ADJ
fcis-6362	96	5	data	datum	NOUN
fcis-6362	96	6	,	,	PUNCT
fcis-6362	96	7	prefix	prefix	NOUN
fcis-6362	96	8	-	-	PUNCT
fcis-6362	96	9	tuning	tuning	NOUN
fcis-6362	96	10	outperforms	outperform	NOUN
fcis-6362	96	11	fine	fine	ADV
fcis-6362	96	12	-	-	PUNCT
fcis-6362	96	13	tuning	tuning	NOUN
fcis-6362	96	14	and	and	CCONJ
fcis-6362	96	15	exhibits	exhibit	VERB
fcis-6362	96	16	superior	superior	ADJ
fcis-6362	96	17	extrapolation	extrapolation	NOUN
fcis-6362	96	18	capabilities	capability	NOUN
fcis-6362	96	19	to	to	ADP
fcis-6362	96	20	examples	example	NOUN
fcis-6362	96	21	featuring	feature	VERB
fcis-6362	96	22	topics	topic	NOUN
fcis-6362	96	23	not	not	PART
fcis-6362	96	24	seen	see	VERB
fcis-6362	96	25	during	during	ADP
fcis-6362	96	26	training	training	NOUN
fcis-6362	96	27	.	.	PUNCT
fcis-6362	97	1	izacard	izacard	VERB
fcis-6362	97	2	et	et	PROPN
fcis-6362	97	3	al	al	PROPN
fcis-6362	98	1	[	[	X
fcis-6362	98	2	12	12	NUM
fcis-6362	98	3	]	]	PUNCT
fcis-6362	98	4	.	.	PUNCT
fcis-6362	99	1	present	present	PROPN
fcis-6362	99	2	atlas	atlas	PROPN
fcis-6362	99	3	,	,	PUNCT
fcis-6362	99	4	a	a	DET
fcis-6362	99	5	carefully	carefully	ADV
fcis-6362	99	6	designed	design	VERB
fcis-6362	99	7	and	and	CCONJ
fcis-6362	99	8	pre	pre	ADJ
fcis-6362	99	9	-	-	ADJ
fcis-6362	99	10	trained	train	VERB
fcis-6362	99	11	retrieval	retrieval	NOUN
fcis-6362	99	12	augmented	augment	VERB
fcis-6362	99	13	language	language	NOUN
fcis-6362	99	14	model	model	NOUN
fcis-6362	99	15	able	able	ADJ
fcis-6362	99	16	to	to	PART
fcis-6362	99	17	learn	learn	VERB
fcis-6362	99	18	knowledge	knowledge	NOUN
fcis-6362	99	19	intensive	intensive	ADJ
fcis-6362	99	20	tasks	task	NOUN
fcis-6362	99	21	with	with	ADP
fcis-6362	99	22	very	very	ADV
fcis-6362	99	23	few	few	ADJ
fcis-6362	99	24	training	training	NOUN
fcis-6362	99	25	examples	example	NOUN
fcis-6362	99	26	.	.	PUNCT
fcis-6362	100	1	kojima	kojima	PROPN
fcis-6362	100	2	et	et	PROPN
fcis-6362	100	3	al	al	PROPN
fcis-6362	101	1	[	[	X
fcis-6362	101	2	13	13	NUM
fcis-6362	101	3	]	]	PUNCT
fcis-6362	101	4	.	.	PUNCT
fcis-6362	102	1	used	use	VERB
fcis-6362	102	2	chain	chain	NOUN
fcis-6362	102	3	of	of	ADP
fcis-6362	102	4	thought	thought	NOUN
fcis-6362	102	5	(	(	PUNCT
fcis-6362	102	6	cot	cot	NOUN
fcis-6362	102	7	)	)	PUNCT
fcis-6362	102	8	prompting	prompt	VERB
fcis-6362	102	9	,	,	PUNCT
fcis-6362	102	10	a	a	DET
fcis-6362	102	11	recent	recent	ADJ
fcis-6362	102	12	technique	technique	NOUN
fcis-6362	102	13	for	for	ADP
fcis-6362	102	14	eliciting	elicit	VERB
fcis-6362	102	15	complex	complex	ADJ
fcis-6362	102	16	multi	multi	ADJ
fcis-6362	102	17	-	-	ADJ
fcis-6362	102	18	step	step	ADJ
fcis-6362	102	19	reasoning	reasoning	NOUN
fcis-6362	102	20	through	through	ADP
fcis-6362	102	21	step	step	NOUN
fcis-6362	102	22	-	-	PUNCT
fcis-6362	102	23	by	by	ADP
fcis-6362	102	24	-	-	PUNCT
fcis-6362	102	25	step	step	NOUN
fcis-6362	102	26	answer	answer	NOUN
fcis-6362	102	27	examples	example	NOUN
fcis-6362	102	28	,	,	PUNCT
fcis-6362	102	29	achieved	achieve	VERB
fcis-6362	102	30	the	the	DET
fcis-6362	102	31	state	state	NOUN
fcis-6362	102	32	-	-	PUNCT
fcis-6362	102	33	of	of	ADP
fcis-6362	102	34	-	-	PUNCT
fcis-6362	102	35	the	the	DET
fcis-6362	102	36	-	-	PUNCT
fcis-6362	102	37	art	art	NOUN
fcis-6362	102	38	performances	performance	NOUN
fcis-6362	102	39	in	in	ADP
fcis-6362	102	40	arithmetics	arithmetic	NOUN
fcis-6362	102	41	and	and	CCONJ
fcis-6362	102	42	symbolic	symbolic	ADJ
fcis-6362	102	43	reasoning	reasoning	NOUN
fcis-6362	102	44	.	.	PUNCT
fcis-6362	103	1	169	169	NUM
fcis-6362	103	2	due	due	ADJ
fcis-6362	103	3	to	to	ADP
fcis-6362	103	4	prompt	prompt	VERB
fcis-6362	103	5	learning	learning	NOUN
fcis-6362	103	6	's	's	PART
fcis-6362	103	7	direct	direct	ADJ
fcis-6362	103	8	utilization	utilization	NOUN
fcis-6362	103	9	of	of	ADP
fcis-6362	103	10	the	the	DET
fcis-6362	103	11	inherent	inherent	ADJ
fcis-6362	103	12	capabilities	capability	NOUN
fcis-6362	103	13	of	of	ADP
fcis-6362	103	14	upstream	upstream	ADJ
fcis-6362	103	15	networks	network	NOUN
fcis-6362	103	16	,	,	PUNCT
fcis-6362	103	17	many	many	ADJ
fcis-6362	103	18	research	research	NOUN
fcis-6362	103	19	hotspots	hotspot	NOUN
fcis-6362	103	20	in	in	ADP
fcis-6362	103	21	the	the	DET
fcis-6362	103	22	"	"	PUNCT
fcis-6362	103	23	pre	pre	ADJ
fcis-6362	103	24	-	-	ADJ
fcis-6362	103	25	train	train	ADJ
fcis-6362	103	26	,	,	PUNCT
fcis-6362	103	27	fine	fine	ADJ
fcis-6362	103	28	-	-	PUNCT
fcis-6362	103	29	tune	tune	NOUN
fcis-6362	103	30	"	"	PUNCT
fcis-6362	103	31	paradigm	paradigm	NOUN
fcis-6362	103	32	have	have	AUX
fcis-6362	103	33	gradually	gradually	ADV
fcis-6362	103	34	faded	fade	VERB
fcis-6362	103	35	in	in	ADP
fcis-6362	103	36	prompt	prompt	ADJ
fcis-6362	103	37	learning	learning	NOUN
fcis-6362	103	38	research	research	NOUN
fcis-6362	103	39	,	,	PUNCT
fcis-6362	103	40	such	such	ADJ
fcis-6362	103	41	as	as	ADP
fcis-6362	103	42	methods	method	NOUN
fcis-6362	103	43	that	that	PRON
fcis-6362	103	44	use	use	VERB
fcis-6362	103	45	downstream	downstream	ADJ
fcis-6362	103	46	networks	network	NOUN
fcis-6362	103	47	to	to	ADP
fcis-6362	103	48	concatenate	concatenate	VERB
fcis-6362	103	49	upstream	upstream	ADJ
fcis-6362	103	50	networks	network	NOUN
fcis-6362	103	51	,	,	PUNCT
fcis-6362	103	52	train	train	VERB
fcis-6362	103	53	heterogeneous	heterogeneous	ADJ
fcis-6362	103	54	networks	network	NOUN
fcis-6362	103	55	in	in	ADP
fcis-6362	103	56	parallel	parallel	NOUN
fcis-6362	103	57	,	,	PUNCT
fcis-6362	103	58	and	and	CCONJ
fcis-6362	103	59	adjust	adjust	VERB
fcis-6362	103	60	loss	loss	NOUN
fcis-6362	103	61	functions	function	NOUN
fcis-6362	103	62	.	.	PUNCT
fcis-6362	104	1	the	the	DET
fcis-6362	104	2	research	research	NOUN
fcis-6362	104	3	focus	focus	NOUN
fcis-6362	104	4	in	in	ADP
fcis-6362	104	5	prompt	prompt	ADJ
fcis-6362	104	6	learning	learning	NOUN
fcis-6362	104	7	has	have	AUX
fcis-6362	104	8	shifted	shift	VERB
fcis-6362	104	9	towards	towards	ADP
fcis-6362	104	10	how	how	SCONJ
fcis-6362	104	11	to	to	PART
fcis-6362	104	12	leverage	leverage	VERB
fcis-6362	104	13	the	the	DET
fcis-6362	104	14	capabilities	capability	NOUN
fcis-6362	104	15	of	of	ADP
fcis-6362	104	16	large	large	ADJ
fcis-6362	104	17	-	-	PUNCT
fcis-6362	104	18	scale	scale	NOUN
fcis-6362	104	19	language	language	NOUN
fcis-6362	104	20	models	model	NOUN
fcis-6362	104	21	using	use	VERB
fcis-6362	104	22	prompts	prompt	NOUN
fcis-6362	104	23	.	.	PUNCT
fcis-6362	105	1	schick	schick	NOUN
fcis-6362	105	2	et	et	PROPN
fcis-6362	105	3	al	al	PROPN
fcis-6362	106	1	[	[	X
fcis-6362	106	2	14	14	NUM
fcis-6362	106	3	]	]	PUNCT
fcis-6362	106	4	.	.	PUNCT
fcis-6362	107	1	propose	propose	VERB
fcis-6362	107	2	a	a	DET
fcis-6362	107	3	cloze	cloze	NOUN
fcis-6362	107	4	-	-	PUNCT
fcis-6362	107	5	style	style	NOUN
fcis-6362	107	6	prompt	prompt	NOUN
fcis-6362	107	7	-	-	PUNCT
fcis-6362	107	8	based	base	VERB
fcis-6362	107	9	fine	fine	ADJ
fcis-6362	107	10	-	-	PUNCT
fcis-6362	107	11	tuning	tune	VERB
fcis-6362	107	12	method	method	NOUN
fcis-6362	107	13	called	call	VERB
fcis-6362	107	14	pattern	pattern	NOUN
fcis-6362	107	15	exploiting	exploit	VERB
fcis-6362	107	16	training	training	NOUN
fcis-6362	107	17	(	(	PUNCT
fcis-6362	107	18	pet	pet	NOUN
fcis-6362	107	19	)	)	PUNCT
fcis-6362	107	20	.	.	PUNCT
fcis-6362	108	1	pet	pet	PROPN
fcis-6362	108	2	is	be	AUX
fcis-6362	108	3	a	a	DET
fcis-6362	108	4	semi	semi	ADJ
fcis-6362	108	5	-	-	ADJ
fcis-6362	108	6	supervised	supervised	ADJ
fcis-6362	108	7	training	training	NOUN
fcis-6362	108	8	procedure	procedure	NOUN
fcis-6362	108	9	that	that	PRON
fcis-6362	108	10	redefines	redefine	VERB
fcis-6362	108	11	input	input	NOUN
fcis-6362	108	12	examples	example	NOUN
fcis-6362	108	13	as	as	ADP
fcis-6362	108	14	cloze	cloze	NOUN
fcis-6362	108	15	-	-	PUNCT
fcis-6362	108	16	style	style	NOUN
fcis-6362	108	17	phrases	phrase	NOUN
fcis-6362	108	18	to	to	PART
fcis-6362	108	19	help	help	VERB
fcis-6362	108	20	language	language	NOUN
fcis-6362	108	21	models	model	NOUN
fcis-6362	108	22	understand	understand	VERB
fcis-6362	108	23	the	the	DET
fcis-6362	108	24	given	give	VERB
fcis-6362	108	25	task	task	NOUN
fcis-6362	108	26	.	.	PUNCT
fcis-6362	109	1	these	these	DET
fcis-6362	109	2	phrases	phrase	NOUN
fcis-6362	109	3	are	be	AUX
fcis-6362	109	4	used	use	VERB
fcis-6362	109	5	to	to	PART
fcis-6362	109	6	assign	assign	VERB
fcis-6362	109	7	soft	soft	ADJ
fcis-6362	109	8	labels	label	NOUN
fcis-6362	109	9	to	to	ADP
fcis-6362	109	10	a	a	DET
fcis-6362	109	11	large	large	ADJ
fcis-6362	109	12	number	number	NOUN
fcis-6362	109	13	of	of	ADP
fcis-6362	109	14	unlabeled	unlabeled	ADJ
fcis-6362	109	15	examples	example	NOUN
fcis-6362	109	16	.	.	PUNCT
fcis-6362	110	1	finally	finally	ADV
fcis-6362	110	2	,	,	PUNCT
fcis-6362	110	3	standard	standard	ADJ
fcis-6362	110	4	supervised	supervised	ADJ
fcis-6362	110	5	training	training	NOUN
fcis-6362	110	6	is	be	AUX
fcis-6362	110	7	performed	perform	VERB
fcis-6362	110	8	on	on	ADP
fcis-6362	110	9	the	the	DET
fcis-6362	110	10	resulting	result	VERB
fcis-6362	110	11	training	training	NOUN
fcis-6362	110	12	set	set	NOUN
fcis-6362	110	13	.	.	PUNCT
fcis-6362	111	1	for	for	ADP
fcis-6362	111	2	several	several	ADJ
fcis-6362	111	3	tasks	task	NOUN
fcis-6362	111	4	and	and	CCONJ
fcis-6362	111	5	languages	language	NOUN
fcis-6362	111	6	,	,	PUNCT
fcis-6362	111	7	pet	pet	ADJ
fcis-6362	111	8	significantly	significantly	ADV
fcis-6362	111	9	outperforms	outperform	VERB
fcis-6362	111	10	supervised	supervised	ADJ
fcis-6362	111	11	training	training	NOUN
fcis-6362	111	12	and	and	CCONJ
fcis-6362	111	13	strong	strong	ADJ
fcis-6362	111	14	semi	semi	ADJ
fcis-6362	111	15	-	-	ADJ
fcis-6362	111	16	supervised	supervised	ADJ
fcis-6362	111	17	methods	method	NOUN
fcis-6362	111	18	in	in	ADP
fcis-6362	111	19	low	low	ADJ
fcis-6362	111	20	-	-	PUNCT
fcis-6362	111	21	resource	resource	NOUN
fcis-6362	111	22	settings	setting	NOUN
fcis-6362	111	23	.	.	PUNCT
fcis-6362	112	1	gao	gao	PROPN
fcis-6362	112	2	et	et	PROPN
fcis-6362	112	3	al	al	PROPN
fcis-6362	113	1	[	[	X
fcis-6362	113	2	15	15	NUM
fcis-6362	113	3	]	]	PUNCT
fcis-6362	113	4	.	.	PUNCT
fcis-6362	114	1	utilized	utilize	VERB
fcis-6362	114	2	prompt	prompt	NOUN
fcis-6362	114	3	-	-	PUNCT
fcis-6362	114	4	based	base	VERB
fcis-6362	114	5	fine	fine	ADJ
fcis-6362	114	6	-	-	PUNCT
fcis-6362	114	7	tuning	tuning	NOUN
fcis-6362	114	8	,	,	PUNCT
fcis-6362	114	9	developed	develop	VERB
fcis-6362	114	10	a	a	DET
fcis-6362	114	11	novel	novel	ADJ
fcis-6362	114	12	pipeline	pipeline	NOUN
fcis-6362	114	13	for	for	ADP
fcis-6362	114	14	automating	automate	VERB
fcis-6362	114	15	prompt	prompt	ADJ
fcis-6362	114	16	generation	generation	NOUN
fcis-6362	114	17	.	.	PUNCT
fcis-6362	115	1	moreover	moreover	ADV
fcis-6362	115	2	,	,	PUNCT
fcis-6362	115	3	they	they	PRON
fcis-6362	115	4	have	have	AUX
fcis-6362	115	5	devised	devise	VERB
fcis-6362	115	6	a	a	DET
fcis-6362	115	7	refined	refined	ADJ
fcis-6362	115	8	approach	approach	NOUN
fcis-6362	115	9	for	for	ADP
fcis-6362	115	10	selectively	selectively	ADV
fcis-6362	115	11	and	and	CCONJ
fcis-6362	115	12	dynamically	dynamically	ADV
fcis-6362	115	13	integrating	integrate	VERB
fcis-6362	115	14	demonstrations	demonstration	NOUN
fcis-6362	115	15	into	into	ADP
fcis-6362	115	16	each	each	DET
fcis-6362	115	17	context	context	NOUN
fcis-6362	115	18	.	.	PUNCT
fcis-6362	116	1	results	result	NOUN
fcis-6362	116	2	show	show	VERB
fcis-6362	116	3	that	that	SCONJ
fcis-6362	116	4	it	it	PRON
fcis-6362	116	5	significantly	significantly	ADV
fcis-6362	116	6	surpasses	surpass	VERB
fcis-6362	116	7	standard	standard	ADJ
fcis-6362	116	8	fine	fine	ADJ
fcis-6362	116	9	-	-	PUNCT
fcis-6362	116	10	tuning	tune	VERB
fcis-6362	116	11	procedures	procedure	NOUN
fcis-6362	116	12	in	in	ADP
fcis-6362	116	13	low	low	ADJ
fcis-6362	116	14	-	-	PUNCT
fcis-6362	116	15	resource	resource	NOUN
fcis-6362	116	16	scenarios	scenario	NOUN
fcis-6362	116	17	,	,	PUNCT
fcis-6362	116	18	achieving	achieve	VERB
fcis-6362	116	19	up	up	ADP
fcis-6362	116	20	to	to	ADP
fcis-6362	116	21	a	a	DET
fcis-6362	116	22	30	30	NUM
fcis-6362	116	23	%	%	NOUN
fcis-6362	116	24	absolute	absolute	ADJ
fcis-6362	116	25	improvement	improvement	NOUN
fcis-6362	116	26	and	and	CCONJ
fcis-6362	116	27	an	an	DET
fcis-6362	116	28	average	average	NOUN
fcis-6362	116	29	of	of	ADP
fcis-6362	116	30	11	11	NUM
fcis-6362	116	31	%	%	NOUN
fcis-6362	116	32	across	across	ADP
fcis-6362	116	33	all	all	DET
fcis-6362	116	34	tasks	task	NOUN
fcis-6362	116	35	.	.	PUNCT
fcis-6362	117	1	autoprompt	autoprompt	PROPN
fcis-6362	117	2	was	be	AUX
fcis-6362	117	3	developed	develop	VERB
fcis-6362	117	4	by	by	ADP
fcis-6362	117	5	shin	shin	PROPN
fcis-6362	117	6	et	et	NOUN
fcis-6362	117	7	al[16	al[16	PROPN
fcis-6362	117	8	]	]	X
fcis-6362	117	9	.	.	PUNCT
fcis-6362	118	1	as	as	ADP
fcis-6362	118	2	an	an	DET
fcis-6362	118	3	automated	automate	VERB
fcis-6362	118	4	approach	approach	NOUN
fcis-6362	118	5	to	to	ADP
fcis-6362	118	6	generating	generate	VERB
fcis-6362	118	7	prompts	prompt	NOUN
fcis-6362	118	8	for	for	ADP
fcis-6362	118	9	a	a	DET
fcis-6362	118	10	wide	wide	ADJ
fcis-6362	118	11	range	range	NOUN
fcis-6362	118	12	of	of	ADP
fcis-6362	118	13	tasks	task	NOUN
fcis-6362	118	14	,	,	PUNCT
fcis-6362	118	15	utilizing	utilize	VERB
fcis-6362	118	16	a	a	DET
fcis-6362	118	17	gradient	gradient	NOUN
fcis-6362	118	18	-	-	PUNCT
fcis-6362	118	19	guided	guide	VERB
fcis-6362	118	20	search	search	NOUN
fcis-6362	118	21	.	.	PUNCT
fcis-6362	119	1	with	with	ADP
fcis-6362	119	2	the	the	DET
fcis-6362	119	3	help	help	NOUN
fcis-6362	119	4	of	of	ADP
fcis-6362	119	5	autoprompt	autoprompt	NOUN
fcis-6362	119	6	,	,	PUNCT
fcis-6362	119	7	masked	mask	VERB
fcis-6362	119	8	language	language	NOUN
fcis-6362	119	9	models	model	NOUN
fcis-6362	119	10	(	(	PUNCT
fcis-6362	119	11	mlms	mlm	NOUN
fcis-6362	119	12	)	)	PUNCT
fcis-6362	119	13	possess	possess	VERB
fcis-6362	119	14	an	an	DET
fcis-6362	119	15	innate	innate	ADJ
fcis-6362	119	16	ability	ability	NOUN
fcis-6362	119	17	to	to	PART
fcis-6362	119	18	carry	carry	VERB
fcis-6362	119	19	out	out	ADP
fcis-6362	119	20	sentiment	sentiment	NOUN
fcis-6362	119	21	analysis	analysis	NOUN
fcis-6362	119	22	and	and	CCONJ
fcis-6362	119	23	natural	natural	ADJ
fcis-6362	119	24	language	language	NOUN
fcis-6362	119	25	inference	inference	NOUN
fcis-6362	119	26	,	,	PUNCT
fcis-6362	119	27	without	without	ADP
fcis-6362	119	28	any	any	DET
fcis-6362	119	29	additional	additional	ADJ
fcis-6362	119	30	parameters	parameter	NOUN
fcis-6362	119	31	or	or	CCONJ
fcis-6362	119	32	fine	fine	ADV
fcis-6362	119	33	-	-	PUNCT
fcis-6362	119	34	tuning	tuning	NOUN
fcis-6362	119	35	.	.	PUNCT
fcis-6362	120	1	liu	liu	PROPN
fcis-6362	120	2	et	et	PROPN
fcis-6362	120	3	al[17	al[17	PROPN
fcis-6362	120	4	]	]	PUNCT
fcis-6362	120	5	.	.	PUNCT
fcis-6362	120	6	proposed	propose	VERB
fcis-6362	120	7	p-tuning.it	p-tuning.it	PRON
fcis-6362	120	8	trains	train	VERB
fcis-6362	120	9	several	several	ADJ
fcis-6362	120	10	prompt	prompt	ADJ
fcis-6362	120	11	vectors	vector	NOUN
fcis-6362	120	12	using	use	VERB
fcis-6362	120	13	regular	regular	ADJ
fcis-6362	120	14	gradient	gradient	ADJ
fcis-6362	120	15	descent	descent	NOUN
fcis-6362	120	16	,	,	PUNCT
fcis-6362	120	17	and	and	CCONJ
fcis-6362	120	18	use	use	VERB
fcis-6362	120	19	an	an	DET
fcis-6362	120	20	lstm	lstm	NOUN
fcis-6362	120	21	to	to	PART
fcis-6362	120	22	generate	generate	VERB
fcis-6362	120	23	a	a	DET
fcis-6362	120	24	final	final	ADJ
fcis-6362	120	25	continuous	continuous	ADJ
fcis-6362	120	26	template	template	NOUN
fcis-6362	120	27	from	from	ADP
fcis-6362	120	28	these	these	DET
fcis-6362	120	29	prompt	prompt	ADJ
fcis-6362	120	30	vectors	vector	NOUN
fcis-6362	120	31	.	.	PUNCT
fcis-6362	121	1	additionally	additionally	ADV
fcis-6362	121	2	,	,	PUNCT
fcis-6362	121	3	for	for	ADP
fcis-6362	121	4	certain	certain	ADJ
fcis-6362	121	5	keywords	keyword	NOUN
fcis-6362	121	6	in	in	ADP
fcis-6362	121	7	the	the	DET
fcis-6362	121	8	input	input	NOUN
fcis-6362	121	9	questions	question	NOUN
fcis-6362	121	10	,	,	PUNCT
fcis-6362	121	11	preserve	preserve	VERB
fcis-6362	121	12	their	their	PRON
fcis-6362	121	13	tokens	token	NOUN
fcis-6362	121	14	in	in	ADP
fcis-6362	121	15	the	the	DET
fcis-6362	121	16	template	template	NOUN
fcis-6362	121	17	.	.	PUNCT
fcis-6362	122	1	this	this	DET
fcis-6362	122	2	approach	approach	NOUN
fcis-6362	122	3	achieves	achieve	VERB
fcis-6362	122	4	better	well	ADJ
fcis-6362	122	5	results	result	NOUN
fcis-6362	122	6	than	than	ADP
fcis-6362	122	7	both	both	CCONJ
fcis-6362	122	8	fine	fine	ADV
fcis-6362	122	9	-	-	PUNCT
fcis-6362	122	10	tuning	tuning	NOUN
fcis-6362	122	11	and	and	CCONJ
fcis-6362	122	12	manually	manually	ADV
fcis-6362	122	13	designed	design	VERB
fcis-6362	122	14	prompt	prompt	NOUN
fcis-6362	122	15	-	-	PUNCT
fcis-6362	122	16	based	base	VERB
fcis-6362	122	17	methods	method	NOUN
fcis-6362	122	18	on	on	ADP
fcis-6362	122	19	superglue	superglue	NOUN
fcis-6362	122	20	and	and	CCONJ
fcis-6362	122	21	some	some	DET
fcis-6362	122	22	nlu	nlu	NOUN
fcis-6362	122	23	tasks	task	NOUN
fcis-6362	122	24	.	.	PUNCT
fcis-6362	123	1	in	in	ADP
fcis-6362	123	2	addition	addition	NOUN
fcis-6362	123	3	to	to	ADP
fcis-6362	123	4	prompt	prompt	ADJ
fcis-6362	123	5	engineering	engineering	NOUN
fcis-6362	123	6	,	,	PUNCT
fcis-6362	123	7	another	another	DET
fcis-6362	123	8	important	important	ADJ
fcis-6362	123	9	component	component	NOUN
fcis-6362	123	10	of	of	ADP
fcis-6362	123	11	prompt	prompt	ADJ
fcis-6362	123	12	learning	learning	NOUN
fcis-6362	123	13	is	be	AUX
fcis-6362	123	14	answer	answer	ADJ
fcis-6362	123	15	engineering	engineering	NOUN
fcis-6362	123	16	.	.	PUNCT
fcis-6362	124	1	unlike	unlike	ADP
fcis-6362	124	2	traditional	traditional	ADJ
fcis-6362	124	3	label	label	NOUN
fcis-6362	124	4	-	-	PUNCT
fcis-6362	124	5	based	base	VERB
fcis-6362	124	6	learning	learning	NOUN
fcis-6362	124	7	,	,	PUNCT
fcis-6362	124	8	the	the	DET
fcis-6362	124	9	learning	learn	VERB
fcis-6362	124	10	objective	objective	NOUN
fcis-6362	124	11	of	of	ADP
fcis-6362	124	12	prompt	prompt	ADJ
fcis-6362	124	13	learning	learning	NOUN
fcis-6362	124	14	is	be	AUX
fcis-6362	124	15	no	no	ADV
fcis-6362	124	16	longer	long	ADV
fcis-6362	124	17	a	a	DET
fcis-6362	124	18	specific	specific	ADJ
fcis-6362	124	19	vector	vector	NOUN
fcis-6362	124	20	,	,	PUNCT
fcis-6362	124	21	but	but	CCONJ
fcis-6362	124	22	a	a	DET
fcis-6362	124	23	answer	answer	NOUN
fcis-6362	124	24	space	space	NOUN
fcis-6362	124	25	z	z	NOUN
fcis-6362	124	26	that	that	PRON
fcis-6362	124	27	is	be	AUX
fcis-6362	124	28	mapped	map	VERB
fcis-6362	124	29	from	from	ADP
fcis-6362	124	30	the	the	DET
fcis-6362	124	31	label	label	NOUN
fcis-6362	124	32	y.	y.	NOUN
fcis-6362	124	33	some	some	DET
fcis-6362	124	34	work	work	NOUN
fcis-6362	124	35	manually	manually	ADV
fcis-6362	124	36	design	design	VERB
fcis-6362	124	37	the	the	DET
fcis-6362	124	38	space	space	NOUN
fcis-6362	124	39	of	of	ADP
fcis-6362	124	40	potential	potential	ADJ
fcis-6362	124	41	answers	answer	NOUN
fcis-6362	124	42	z	z	NOUN
fcis-6362	124	43	and	and	CCONJ
fcis-6362	124	44	its	its	PRON
fcis-6362	124	45	mapping	mapping	NOUN
fcis-6362	124	46	to	to	ADP
fcis-6362	124	47	y.	y.	PROPN
fcis-6362	124	48	yin	yin	PROPN
fcis-6362	124	49	et	et	NOUN
fcis-6362	124	50	al[18	al[18	PROPN
fcis-6362	124	51	]	]	PUNCT
fcis-6362	124	52	.	.	PUNCT
fcis-6362	125	1	manually	manually	ADV
fcis-6362	125	2	design	design	NOUN
fcis-6362	125	3	lists	list	NOUN
fcis-6362	125	4	of	of	ADP
fcis-6362	125	5	words	word	NOUN
fcis-6362	125	6	relating	relate	VERB
fcis-6362	125	7	to	to	ADP
fcis-6362	125	8	relevant	relevant	ADJ
fcis-6362	125	9	topics	topic	NOUN
fcis-6362	125	10	(	(	PUNCT
fcis-6362	125	11	“	"	PUNCT
fcis-6362	125	12	health	health	NOUN
fcis-6362	125	13	”	"	PUNCT
fcis-6362	125	14	,	,	PUNCT
fcis-6362	125	15	“	"	PUNCT
fcis-6362	125	16	finance	finance	NOUN
fcis-6362	125	17	”	"	PUNCT
fcis-6362	125	18	,	,	PUNCT
fcis-6362	125	19	“	"	PUNCT
fcis-6362	125	20	politics	politic	NOUN
fcis-6362	125	21	”	"	PUNCT
fcis-6362	125	22	,	,	PUNCT
fcis-6362	125	23	“	"	PUNCT
fcis-6362	125	24	sports	sport	NOUN
fcis-6362	125	25	”	"	PUNCT
fcis-6362	125	26	,	,	PUNCT
fcis-6362	125	27	etc	etc	X
fcis-6362	125	28	.	.	X
fcis-6362	125	29	)	)	PUNCT
fcis-6362	125	30	,	,	PUNCT
fcis-6362	125	31	emotions	emotion	NOUN
fcis-6362	125	32	(	(	PUNCT
fcis-6362	125	33	“	"	PUNCT
fcis-6362	125	34	anger	anger	NOUN
fcis-6362	125	35	”	"	PUNCT
fcis-6362	125	36	,	,	PUNCT
fcis-6362	125	37	“	"	PUNCT
fcis-6362	125	38	joy	joy	NOUN
fcis-6362	125	39	”	"	PUNCT
fcis-6362	125	40	,	,	PUNCT
fcis-6362	125	41	“	"	PUNCT
fcis-6362	125	42	sadness	sadness	NOUN
fcis-6362	125	43	”	"	PUNCT
fcis-6362	125	44	,	,	PUNCT
fcis-6362	125	45	“	"	PUNCT
fcis-6362	125	46	fear	fear	NOUN
fcis-6362	125	47	”	"	PUNCT
fcis-6362	125	48	,	,	PUNCT
fcis-6362	125	49	etc	etc	X
fcis-6362	125	50	.	.	X
fcis-6362	125	51	)	)	PUNCT
fcis-6362	125	52	,	,	PUNCT
fcis-6362	125	53	or	or	CCONJ
fcis-6362	125	54	other	other	ADJ
fcis-6362	125	55	aspects	aspect	NOUN
fcis-6362	125	56	of	of	ADP
fcis-6362	125	57	the	the	DET
fcis-6362	125	58	input	input	NOUN
fcis-6362	125	59	text	text	NOUN
fcis-6362	125	60	to	to	PART
fcis-6362	125	61	be	be	AUX
fcis-6362	125	62	classified	classify	VERB
fcis-6362	125	63	.	.	PUNCT
fcis-6362	126	1	obviously	obviously	ADV
fcis-6362	126	2	,	,	PUNCT
fcis-6362	126	3	there	there	PRON
fcis-6362	126	4	are	be	VERB
fcis-6362	126	5	limitations	limitation	NOUN
fcis-6362	126	6	to	to	AUX
fcis-6362	126	7	manually	manually	ADV
fcis-6362	126	8	constructing	construct	VERB
fcis-6362	126	9	mappings	mapping	NOUN
fcis-6362	126	10	.	.	PUNCT
fcis-6362	127	1	some	some	DET
fcis-6362	127	2	work	work	NOUN
fcis-6362	127	3	focuses	focus	VERB
fcis-6362	127	4	on	on	ADP
fcis-6362	127	5	automatic	automatic	ADJ
fcis-6362	127	6	answer	answer	NOUN
fcis-6362	127	7	search	search	NOUN
fcis-6362	127	8	,	,	PUNCT
fcis-6362	127	9	albeit	albeit	SCONJ
fcis-6362	127	10	less	less	ADJ
fcis-6362	127	11	than	than	ADP
fcis-6362	127	12	that	that	PRON
fcis-6362	127	13	on	on	ADP
fcis-6362	127	14	searching	search	VERB
fcis-6362	127	15	for	for	ADP
fcis-6362	127	16	ideal	ideal	ADJ
fcis-6362	127	17	prompts	prompt	NOUN
fcis-6362	127	18	.	.	PUNCT
fcis-6362	128	1	these	these	DET
fcis-6362	128	2	work	work	NOUN
fcis-6362	128	3	on	on	ADP
fcis-6362	128	4	both	both	CCONJ
fcis-6362	128	5	discrete	discrete	ADJ
fcis-6362	128	6	answer	answer	NOUN
fcis-6362	128	7	spaces	space	NOUN
fcis-6362	128	8	and	and	CCONJ
fcis-6362	128	9	continuous	continuous	ADJ
fcis-6362	128	10	answer	answer	NOUN
fcis-6362	128	11	spaces	space	NOUN
fcis-6362	128	12	.	.	PUNCT
fcis-6362	129	1	chen	chen	PROPN
fcis-6362	129	2	et	et	PROPN
fcis-6362	129	3	al	al	PROPN
fcis-6362	130	1	[	[	X
fcis-6362	130	2	19	19	NUM
fcis-6362	130	3	]	]	PUNCT
fcis-6362	130	4	.	.	PUNCT
fcis-6362	131	1	introduce	introduce	VERB
fcis-6362	131	2	a	a	DET
fcis-6362	131	3	novel	novel	ADJ
fcis-6362	131	4	approach	approach	NOUN
fcis-6362	131	5	called	call	VERB
fcis-6362	131	6	knowprompt	knowprompt	ADJ
fcis-6362	131	7	,	,	PUNCT
fcis-6362	131	8	which	which	PRON
fcis-6362	131	9	leverages	leverage	VERB
fcis-6362	131	10	this	this	DET
fcis-6362	131	11	knowledge	knowledge	NOUN
fcis-6362	131	12	through	through	ADP
fcis-6362	131	13	the	the	DET
fcis-6362	131	14	use	use	NOUN
fcis-6362	131	15	of	of	ADP
fcis-6362	131	16	learnable	learnable	ADJ
fcis-6362	131	17	virtual	virtual	ADJ
fcis-6362	131	18	type	type	NOUN
fcis-6362	131	19	words	word	NOUN
fcis-6362	131	20	and	and	CCONJ
fcis-6362	131	21	answer	answer	VERB
fcis-6362	131	22	words	word	NOUN
fcis-6362	131	23	during	during	ADP
fcis-6362	131	24	prompt	prompt	ADJ
fcis-6362	131	25	construction	construction	NOUN
fcis-6362	131	26	,	,	PUNCT
fcis-6362	131	27	resulting	result	VERB
fcis-6362	131	28	in	in	ADP
fcis-6362	131	29	synergistic	synergistic	ADJ
fcis-6362	131	30	optimization	optimization	NOUN
fcis-6362	131	31	.	.	PUNCT
fcis-6362	132	1	the	the	DET
fcis-6362	132	2	goal	goal	NOUN
fcis-6362	132	3	of	of	ADP
fcis-6362	132	4	knowprompt	knowprompt	ADJ
fcis-6362	132	5	is	be	AUX
fcis-6362	132	6	to	to	PART
fcis-6362	132	7	improve	improve	VERB
fcis-6362	132	8	the	the	DET
fcis-6362	132	9	ability	ability	NOUN
fcis-6362	132	10	of	of	ADP
fcis-6362	132	11	our	our	PRON
fcis-6362	132	12	system	system	NOUN
fcis-6362	132	13	to	to	PART
fcis-6362	132	14	identify	identify	VERB
fcis-6362	132	15	relevant	relevant	ADJ
fcis-6362	132	16	relations	relation	NOUN
fcis-6362	132	17	by	by	ADP
fcis-6362	132	18	incorporating	incorporate	VERB
fcis-6362	132	19	latent	latent	ADJ
fcis-6362	132	20	knowledge	knowledge	NOUN
fcis-6362	132	21	present	present	ADJ
fcis-6362	132	22	in	in	ADP
fcis-6362	132	23	the	the	DET
fcis-6362	132	24	relation	relation	NOUN
fcis-6362	132	25	labels	label	NOUN
fcis-6362	132	26	.	.	PUNCT
fcis-6362	133	1	hambardzumyan	hambardzumyan	PROPN
fcis-6362	133	2	et	et	PROPN
fcis-6362	133	3	al	al	PROPN
fcis-6362	134	1	[	[	X
fcis-6362	134	2	20	20	NUM
fcis-6362	134	3	]	]	PUNCT
fcis-6362	134	4	.	.	PUNCT
fcis-6362	135	1	explore	explore	VERB
fcis-6362	135	2	possibility	possibility	NOUN
fcis-6362	135	3	of	of	ADP
fcis-6362	135	4	using	use	VERB
fcis-6362	135	5	soft	soft	ADJ
fcis-6362	135	6	answer	answer	NOUN
fcis-6362	135	7	tokens	token	NOUN
fcis-6362	135	8	which	which	PRON
fcis-6362	135	9	can	can	AUX
fcis-6362	135	10	be	be	AUX
fcis-6362	135	11	optimized	optimize	VERB
fcis-6362	135	12	through	through	ADP
fcis-6362	135	13	gradient	gradient	ADJ
fcis-6362	135	14	descent	descent	NOUN
fcis-6362	135	15	.	.	PUNCT
fcis-6362	136	1	they	they	PRON
fcis-6362	136	2	present	present	VERB
fcis-6362	136	3	an	an	DET
fcis-6362	136	4	alternative	alternative	ADJ
fcis-6362	136	5	approach	approach	NOUN
fcis-6362	136	6	based	base	VERB
fcis-6362	136	7	on	on	ADP
fcis-6362	136	8	adversarial	adversarial	ADJ
fcis-6362	136	9	reprogramming	reprogramming	NOUN
fcis-6362	136	10	,	,	PUNCT
fcis-6362	136	11	which	which	PRON
fcis-6362	136	12	extends	extend	VERB
fcis-6362	136	13	earlier	early	ADJ
fcis-6362	136	14	work	work	NOUN
fcis-6362	136	15	on	on	ADP
fcis-6362	136	16	automatic	automatic	ADJ
fcis-6362	136	17	prompt	prompt	ADJ
fcis-6362	136	18	generation	generation	NOUN
fcis-6362	136	19	.	.	PUNCT
fcis-6362	137	1	3	3	X
fcis-6362	137	2	.	.	X
fcis-6362	137	3	approach	approach	NOUN
fcis-6362	137	4	in	in	ADP
fcis-6362	137	5	traditional	traditional	ADJ
fcis-6362	137	6	supervised	supervised	ADJ
fcis-6362	137	7	learning	learning	NOUN
fcis-6362	137	8	,	,	PUNCT
fcis-6362	137	9	the	the	DET
fcis-6362	137	10	model	model	NOUN
fcis-6362	137	11	takes	take	VERB
fcis-6362	137	12	input	input	NOUN
fcis-6362	137	13	x	x	X
fcis-6362	137	14	and	and	CCONJ
fcis-6362	137	15	outputs	output	NOUN
fcis-6362	137	16	y.	y.	PROPN
fcis-6362	137	17	this	this	DET
fcis-6362	137	18	process	process	NOUN
fcis-6362	137	19	can	can	AUX
fcis-6362	137	20	be	be	AUX
fcis-6362	137	21	seen	see	VERB
fcis-6362	137	22	as	as	ADP
fcis-6362	137	23	computing	compute	VERB
fcis-6362	137	24	𝑃(𝑦|𝑥	𝑃(𝑦|𝑥	PROPN
fcis-6362	137	25	;	;	PUNCT
fcis-6362	138	1	𝜃).prompt	𝜃).prompt	PROPN
fcis-6362	138	2	-	-	PUNCT
fcis-6362	138	3	based	base	VERB
fcis-6362	138	4	learning	learning	NOUN
fcis-6362	138	5	methods	method	NOUN
fcis-6362	138	6	for	for	ADP
fcis-6362	138	7	nlp	nlp	NOUN
fcis-6362	138	8	attempt	attempt	NOUN
fcis-6362	138	9	to	to	PART
fcis-6362	138	10	circumvent	circumvent	VERB
fcis-6362	138	11	this	this	DET
fcis-6362	138	12	issue	issue	NOUN
fcis-6362	138	13	by	by	ADP
fcis-6362	138	14	instead	instead	ADV
fcis-6362	138	15	learning	learn	VERB
fcis-6362	138	16	an	an	DET
fcis-6362	138	17	lm	lm	INTJ
fcis-6362	138	18	that	that	PRON
fcis-6362	138	19	models	model	VERB
fcis-6362	138	20	the	the	DET
fcis-6362	138	21	probability	probability	NOUN
fcis-6362	138	22	𝑃(𝑥	𝑃(𝑥	NOUN
fcis-6362	138	23	;	;	PUNCT
fcis-6362	138	24	𝜃	𝜃	X
fcis-6362	138	25	)	)	PUNCT
fcis-6362	138	26	of	of	ADP
fcis-6362	138	27	text	text	NOUN
fcis-6362	138	28	𝑥	𝑥	VERB
fcis-6362	138	29	itself	itself	PRON
fcis-6362	138	30	and	and	CCONJ
fcis-6362	138	31	using	use	VERB
fcis-6362	138	32	this	this	DET
fcis-6362	138	33	probability	probability	NOUN
fcis-6362	138	34	to	to	PART
fcis-6362	138	35	predict	predict	VERB
fcis-6362	138	36	𝑦	𝑦	NOUN
fcis-6362	138	37	.	.	PUNCT
fcis-6362	139	1	this	this	DET
fcis-6362	139	2	approach	approach	NOUN
fcis-6362	139	3	is	be	AUX
fcis-6362	139	4	more	more	ADV
fcis-6362	139	5	akin	akin	ADJ
fcis-6362	139	6	to	to	ADP
fcis-6362	139	7	communicating	communicate	VERB
fcis-6362	139	8	with	with	ADP
fcis-6362	139	9	a	a	DET
fcis-6362	139	10	human	human	NOUN
fcis-6362	139	11	rather	rather	ADV
fcis-6362	139	12	than	than	ADP
fcis-6362	139	13	debugging	debug	VERB
fcis-6362	139	14	a	a	DET
fcis-6362	139	15	machine	machine	NOUN
fcis-6362	139	16	.	.	PUNCT
fcis-6362	140	1	table	table	NOUN
fcis-6362	140	2	1	1	NUM
fcis-6362	140	3	shows	show	VERB
fcis-6362	140	4	the	the	DET
fcis-6362	140	5	typical	typical	ADJ
fcis-6362	140	6	pipeline	pipeline	NOUN
fcis-6362	140	7	of	of	ADP
fcis-6362	140	8	prompt	prompt	NOUN
fcis-6362	140	9	-	-	PUNCT
fcis-6362	140	10	based	base	VERB
fcis-6362	140	11	learning	learning	NOUN
fcis-6362	140	12	.	.	PUNCT
fcis-6362	141	1	table	table	NOUN
fcis-6362	141	2	1	1	NUM
fcis-6362	141	3	.	.	PUNCT
fcis-6362	142	1	pipeline	pipeline	NOUN
fcis-6362	142	2	of	of	ADP
fcis-6362	142	3	prompt	prompt	NOUN
fcis-6362	142	4	-	-	PUNCT
fcis-6362	142	5	based	base	VERB
fcis-6362	142	6	learning	learning	NOUN
fcis-6362	142	7	name	name	NOUN
fcis-6362	142	8	notation	notation	NOUN
fcis-6362	142	9	example	example	NOUN
fcis-6362	142	10	input	input	NOUN
fcis-6362	142	11	𝑥	𝑥	X
fcis-6362	143	1	i	i	PRON
fcis-6362	143	2	love	love	VERB
fcis-6362	143	3	this	this	DET
fcis-6362	143	4	move	move	NOUN
fcis-6362	143	5	output	output	NOUN
fcis-6362	143	6	𝑦	𝑦	NOUN
fcis-6362	143	7	+	+	NOUN
fcis-6362	143	8	+	+	ADJ
fcis-6362	143	9	(	(	PUNCT
fcis-6362	143	10	very	very	ADV
fcis-6362	143	11	positive	positive	ADJ
fcis-6362	143	12	)	)	PUNCT
fcis-6362	143	13	prompting	prompt	VERB
fcis-6362	143	14	function	function	NOUN
fcis-6362	143	15	𝑓𝑝𝑟𝑜𝑚𝑝𝑡(𝑥	𝑓𝑝𝑟𝑜𝑚𝑝𝑡(𝑥	PROPN
fcis-6362	143	16	)	)	PUNCT
fcis-6362	144	1	[	[	X
fcis-6362	144	2	𝑋	𝑋	X
fcis-6362	144	3	]	]	PUNCT
fcis-6362	144	4	overall	overall	ADV
fcis-6362	144	5	,	,	PUNCT
fcis-6362	144	6	it	it	PRON
fcis-6362	144	7	was	be	AUX
fcis-6362	144	8	a	a	DET
fcis-6362	144	9	[	[	X
fcis-6362	144	10	𝑍	𝑍	NOUN
fcis-6362	144	11	]	]	X
fcis-6362	144	12	movie	movie	NOUN
fcis-6362	144	13	.	.	PUNCT
fcis-6362	145	1	prompt	prompt	ADJ
fcis-6362	145	2	𝑥′	𝑥′	PUNCT
fcis-6362	146	1	i	i	PRON
fcis-6362	146	2	love	love	VERB
fcis-6362	146	3	this	this	DET
fcis-6362	146	4	movie	movie	NOUN
fcis-6362	146	5	.	.	PUNCT
fcis-6362	147	1	overall	overall	ADJ
fcis-6362	147	2	,	,	PUNCT
fcis-6362	147	3	it	it	PRON
fcis-6362	147	4	was	be	AUX
fcis-6362	147	5	a	a	DET
fcis-6362	147	6	[	[	X
fcis-6362	147	7	𝑍	𝑍	ADP
fcis-6362	147	8	]	]	X
fcis-6362	147	9	movie	movie	NOUN
fcis-6362	147	10	.	.	PUNCT
fcis-6362	148	1	filled	fill	VERB
fcis-6362	148	2	prompt	prompt	NOUN
fcis-6362	148	3	𝑓𝑓𝑖𝑙𝑙(𝑥′	𝑓𝑓𝑖𝑙𝑙(𝑥′	PROPN
fcis-6362	148	4	,	,	PUNCT
fcis-6362	148	5	𝑧	𝑧	PART
fcis-6362	148	6	)	)	PUNCT
fcis-6362	148	7	i	i	PRON
fcis-6362	148	8	love	love	VERB
fcis-6362	148	9	this	this	DET
fcis-6362	148	10	movie	movie	NOUN
fcis-6362	148	11	.	.	PUNCT
fcis-6362	149	1	overall	overall	ADJ
fcis-6362	149	2	,	,	PUNCT
fcis-6362	149	3	it	it	PRON
fcis-6362	149	4	was	be	AUX
fcis-6362	149	5	a	a	DET
fcis-6362	149	6	bad	bad	ADJ
fcis-6362	149	7	movie	movie	NOUN
fcis-6362	149	8	.	.	PUNCT
fcis-6362	150	1	answered	answer	VERB
fcis-6362	150	2	prompt	prompt	ADJ
fcis-6362	150	3	𝑓𝑓𝑖𝑙𝑙(𝑥′	𝑓𝑓𝑖𝑙𝑙(𝑥′	PROPN
fcis-6362	150	4	,	,	PUNCT
fcis-6362	150	5	𝑧∗	𝑧∗	PROPN
fcis-6362	150	6	)	)	PUNCT
fcis-6362	151	1	i	i	PRON
fcis-6362	151	2	love	love	VERB
fcis-6362	151	3	this	this	DET
fcis-6362	151	4	movie	movie	NOUN
fcis-6362	151	5	.	.	PUNCT
fcis-6362	152	1	overall	overall	ADJ
fcis-6362	152	2	,	,	PUNCT
fcis-6362	152	3	it	it	PRON
fcis-6362	152	4	was	be	AUX
fcis-6362	152	5	a	a	DET
fcis-6362	152	6	good	good	ADJ
fcis-6362	152	7	movie	movie	NOUN
fcis-6362	152	8	.	.	PUNCT
fcis-6362	153	1	answer	answer	NOUN
fcis-6362	153	2	space	space	NOUN
fcis-6362	153	3	𝑧	𝑧	PRON
fcis-6362	153	4	“	"	PUNCT
fcis-6362	153	5	good	good	ADJ
fcis-6362	153	6	”	"	PUNCT
fcis-6362	153	7	,	,	PUNCT
fcis-6362	153	8	“	"	PUNCT
fcis-6362	153	9	fantastic	fantastic	ADJ
fcis-6362	153	10	”	"	PUNCT
fcis-6362	153	11	,	,	PUNCT
fcis-6362	153	12	“	"	PUNCT
fcis-6362	153	13	boring	boring	ADJ
fcis-6362	153	14	”	"	PUNCT
fcis-6362	153	15	different	different	ADJ
fcis-6362	153	16	templates	template	NOUN
fcis-6362	153	17	can	can	AUX
fcis-6362	153	18	adapt	adapt	VERB
fcis-6362	153	19	to	to	ADP
fcis-6362	153	20	different	different	ADJ
fcis-6362	153	21	downstream	downstream	ADJ
fcis-6362	153	22	tasks	task	NOUN
fcis-6362	153	23	,	,	PUNCT
fcis-6362	153	24	as	as	SCONJ
fcis-6362	153	25	shown	show	VERB
fcis-6362	153	26	in	in	ADP
fcis-6362	153	27	table	table	NOUN
fcis-6362	153	28	2	2	NUM
fcis-6362	153	29	.	.	PUNCT
fcis-6362	153	30	table	table	NOUN
fcis-6362	153	31	2	2	NUM
fcis-6362	153	32	.	.	PUNCT
fcis-6362	153	33	different	different	ADJ
fcis-6362	153	34	template	template	NOUN
fcis-6362	153	35	type	type	NOUN
fcis-6362	153	36	input	input	NOUN
fcis-6362	153	37	template	template	NOUN
fcis-6362	153	38	text	text	NOUN
fcis-6362	153	39	cls	cls	NOUN
fcis-6362	153	40	i	i	PRON
fcis-6362	153	41	love	love	VERB
fcis-6362	153	42	this	this	DET
fcis-6362	153	43	movie	movie	NOUN
fcis-6362	154	1	[	[	X
fcis-6362	154	2	𝑋	𝑋	X
fcis-6362	154	3	]	]	PUNCT
fcis-6362	154	4	the	the	DET
fcis-6362	154	5	movie	movie	NOUN
fcis-6362	154	6	is	be	AUX
fcis-6362	154	7	[	[	X
fcis-6362	154	8	𝑍	𝑍	NOUN
fcis-6362	154	9	]	]	PUNCT
fcis-6362	154	10	.	.	PUNCT
fcis-6362	155	1	text	text	NOUN
fcis-6362	155	2	-	-	PUNCT
fcis-6362	155	3	span	span	NOUN
fcis-6362	155	4	cls	cls	NOUN
fcis-6362	155	5	poor	poor	ADJ
fcis-6362	155	6	service	service	NOUN
fcis-6362	155	7	but	but	CCONJ
fcis-6362	155	8	good	good	ADJ
fcis-6362	155	9	food	food	NOUN
fcis-6362	155	10	.	.	PUNCT
fcis-6362	156	1	[	[	X
fcis-6362	156	2	𝑋	𝑋	X
fcis-6362	156	3	]	]	X
fcis-6362	156	4	what	what	PRON
fcis-6362	156	5	about	about	ADP
fcis-6362	156	6	service	service	NOUN
fcis-6362	156	7	?	?	PUNCT
fcis-6362	157	1	[	[	X
fcis-6362	157	2	𝑍	𝑍	NOUN
fcis-6362	157	3	]	]	PUNCT
fcis-6362	157	4	.	.	PUNCT
fcis-6362	158	1	text	text	NOUN
fcis-6362	158	2	-	-	PUNCT
fcis-6362	158	3	pair	pair	NOUN
fcis-6362	158	4	cls	cls	NOUN
fcis-6362	159	1	[	[	X
fcis-6362	159	2	𝑋1	𝑋1	X
fcis-6362	159	3	]	]	X
fcis-6362	159	4	:	:	PUNCT
fcis-6362	159	5	an	an	DET
fcis-6362	159	6	old	old	ADJ
fcis-6362	159	7	man	man	NOUN
fcis-6362	159	8	with	with	ADP
fcis-6362	159	9	...	...	PUNCT
fcis-6362	160	1	[	[	X
fcis-6362	160	2	𝑋2	𝑋2	X
fcis-6362	160	3	]	]	X
fcis-6362	160	4	:	:	PUNCT
fcis-6362	160	5	a	a	DET
fcis-6362	160	6	man	man	NOUN
fcis-6362	160	7	walks	walk	VERB
fcis-6362	160	8	...	...	PUNCT
fcis-6362	161	1	[	[	X
fcis-6362	161	2	𝑋1	𝑋1	X
fcis-6362	161	3	]	]	PUNCT
fcis-6362	161	4	?	?	PUNCT
fcis-6362	162	1	[	[	X
fcis-6362	162	2	𝑍	𝑍	NOUN
fcis-6362	162	3	]	]	PUNCT
fcis-6362	162	4	,	,	PUNCT
fcis-6362	162	5	[	[	X
fcis-6362	162	6	𝑋2	𝑋2	X
fcis-6362	162	7	]	]	X
fcis-6362	162	8	tagging	tag	VERB
fcis-6362	162	9	[	[	X
fcis-6362	162	10	𝑋1	𝑋1	X
fcis-6362	162	11	]	]	X
fcis-6362	162	12	:	:	PUNCT
fcis-6362	162	13	mike	mike	PROPN
fcis-6362	162	14	went	go	VERB
fcis-6362	162	15	to	to	ADP
fcis-6362	162	16	paris	paris	PROPN
fcis-6362	163	1	[	[	X
fcis-6362	163	2	𝑋2	𝑋2	VERB
fcis-6362	163	3	]	]	X
fcis-6362	163	4	:	:	PUNCT
fcis-6362	163	5	paris	paris	PROPN
fcis-6362	164	1	[	[	X
fcis-6362	164	2	𝑋1][𝑋2	𝑋1][𝑋2	PROPN
fcis-6362	164	3	]	]	X
fcis-6362	164	4	is	be	AUX
fcis-6362	164	5	a	a	DET
fcis-6362	164	6	[	[	X
fcis-6362	164	7	𝑍	𝑍	NOUN
fcis-6362	164	8	]	]	PUNCT
fcis-6362	164	9	entity	entity	NOUN
fcis-6362	164	10	text	text	NOUN
fcis-6362	164	11	generation	generation	NOUN
fcis-6362	164	12	你好	你好	ADP
fcis-6362	164	13	chinese	chinese	ADJ
fcis-6362	164	14	:	:	PUNCT
fcis-6362	165	1	[	[	X
fcis-6362	165	2	𝑋	𝑋	X
fcis-6362	165	3	]	]	X
fcis-6362	165	4	english	english	NOUN
fcis-6362	165	5	:	:	PUNCT
fcis-6362	166	1	[	[	X
fcis-6362	166	2	𝑍	𝑍	NOUN
fcis-6362	166	3	]	]	PUNCT
fcis-6362	166	4	however	however	ADV
fcis-6362	166	5	,	,	PUNCT
fcis-6362	166	6	direct	direct	ADJ
fcis-6362	166	7	application	application	NOUN
fcis-6362	166	8	of	of	ADP
fcis-6362	166	9	manual	manual	ADJ
fcis-6362	166	10	templates	template	NOUN
fcis-6362	166	11	for	for	ADP
fcis-6362	166	12	learning	learn	VERB
fcis-6362	166	13	results	result	NOUN
fcis-6362	166	14	in	in	ADP
fcis-6362	166	15	significant	significant	ADJ
fcis-6362	166	16	performance	performance	NOUN
fcis-6362	166	17	fluctuations	fluctuation	NOUN
fcis-6362	166	18	in	in	ADP
fcis-6362	166	19	the	the	DET
fcis-6362	166	20	model	model	NOUN
fcis-6362	166	21	.	.	PUNCT
fcis-6362	167	1	table	table	NOUN
fcis-6362	167	2	3	3	NUM
fcis-6362	167	3	from	from	ADP
fcis-6362	167	4	the	the	DET
fcis-6362	167	5	work	work	NOUN
fcis-6362	167	6	of	of	ADP
fcis-6362	167	7	liu	liu	PROPN
fcis-6362	167	8	et	et	PROPN
fcis-6362	167	9	al	al	PROPN
fcis-6362	168	1	[	[	X
fcis-6362	168	2	21	21	NUM
fcis-6362	168	3	]	]	PUNCT
fcis-6362	168	4	.	.	PUNCT
fcis-6362	168	5	,	,	PUNCT
fcis-6362	168	6	shows	show	VERB
fcis-6362	168	7	that	that	SCONJ
fcis-6362	168	8	a	a	DET
fcis-6362	168	9	change	change	NOUN
fcis-6362	168	10	in	in	ADP
fcis-6362	168	11	a	a	DET
fcis-6362	168	12	single	single	ADJ
fcis-6362	168	13	word	word	NOUN
fcis-6362	168	14	can	can	AUX
fcis-6362	168	15	have	have	VERB
fcis-6362	168	16	a	a	DET
fcis-6362	168	17	great	great	ADJ
fcis-6362	168	18	impact	impact	NOUN
fcis-6362	168	19	on	on	ADP
fcis-6362	168	20	the	the	DET
fcis-6362	168	21	model	model	NOUN
fcis-6362	168	22	.	.	PUNCT
fcis-6362	169	1	table	table	NOUN
fcis-6362	169	2	3	3	NUM
fcis-6362	169	3	.	.	PUNCT
fcis-6362	169	4	case	case	NOUN
fcis-6362	169	5	study	study	NOUN
fcis-6362	169	6	on	on	ADP
fcis-6362	169	7	lama	lama	PROPN
fcis-6362	169	8	-	-	PUNCT
fcis-6362	169	9	trex	trex	NOUN
fcis-6362	169	10	p17	p17	NOUN
fcis-6362	169	11	with	with	ADP
fcis-6362	169	12	bert	bert	NOUN
fcis-6362	169	13	-	-	PUNCT
fcis-6362	169	14	base	base	NOUN
fcis-6362	169	15	-	-	PUNCT
fcis-6362	169	16	cased	case	VERB
fcis-6362	169	17	prompt	prompt	ADJ
fcis-6362	169	18	p@1	p@1	NOUN
fcis-6362	169	19	[	[	X
fcis-6362	169	20	𝑿	𝑿	X
fcis-6362	169	21	]	]	PUNCT
fcis-6362	169	22	is	be	AUX
fcis-6362	169	23	located	locate	VERB
fcis-6362	169	24	in	in	ADP
fcis-6362	169	25	[	[	X
fcis-6362	169	26	𝒀	𝒀	NOUN
fcis-6362	169	27	]	]	X
fcis-6362	169	28	.	.	PUNCT
fcis-6362	170	1	(	(	PUNCT
fcis-6362	170	2	original	original	ADJ
fcis-6362	170	3	)	)	PUNCT
fcis-6362	170	4	31.29	31.29	NUM
fcis-6362	170	5	[	[	X
fcis-6362	170	6	𝑿	𝑿	X
fcis-6362	170	7	]	]	PUNCT
fcis-6362	170	8	is	be	AUX
fcis-6362	170	9	located	locate	VERB
fcis-6362	170	10	in	in	ADP
fcis-6362	170	11	which	which	DET
fcis-6362	170	12	country	country	NOUN
fcis-6362	170	13	or	or	CCONJ
fcis-6362	170	14	state	state	NOUN
fcis-6362	170	15	?	?	PUNCT
fcis-6362	171	1	[	[	X
fcis-6362	171	2	𝒀	𝒀	X
fcis-6362	171	3	]	]	X
fcis-6362	171	4	.	.	PUNCT
fcis-6362	172	1	19.78	19.78	NUM
fcis-6362	172	2	[	[	X
fcis-6362	172	3	𝑿	𝑿	X
fcis-6362	172	4	]	]	PUNCT
fcis-6362	172	5	is	be	AUX
fcis-6362	172	6	located	locate	VERB
fcis-6362	172	7	in	in	ADP
fcis-6362	172	8	which	which	DET
fcis-6362	172	9	country	country	NOUN
fcis-6362	172	10	?	?	PUNCT
fcis-6362	173	1	[	[	X
fcis-6362	173	2	𝒀	𝒀	X
fcis-6362	173	3	]	]	X
fcis-6362	173	4	.	.	PUNCT
fcis-6362	174	1	31.40	31.40	NUM
fcis-6362	175	1	[	[	X
fcis-6362	175	2	𝑿	𝑿	X
fcis-6362	175	3	]	]	PUNCT
fcis-6362	175	4	is	be	AUX
fcis-6362	175	5	located	locate	VERB
fcis-6362	175	6	in	in	ADP
fcis-6362	175	7	which	which	DET
fcis-6362	175	8	country	country	NOUN
fcis-6362	175	9	?	?	PUNCT
fcis-6362	176	1	in	in	ADP
fcis-6362	176	2	[	[	X
fcis-6362	176	3	𝒀	𝒀	NOUN
fcis-6362	176	4	]	]	X
fcis-6362	176	5	.	.	PUNCT
fcis-6362	177	1	51.08	51.08	NUM
fcis-6362	177	2	the	the	DET
fcis-6362	177	3	same	same	ADJ
fcis-6362	177	4	situation	situation	NOUN
fcis-6362	177	5	also	also	ADV
fcis-6362	177	6	occurs	occur	VERB
fcis-6362	177	7	in	in	ADP
fcis-6362	177	8	the	the	DET
fcis-6362	177	9	answer	answer	NOUN
fcis-6362	177	10	space	space	NOUN
fcis-6362	177	11	,	,	PUNCT
fcis-6362	177	12	where	where	SCONJ
fcis-6362	177	13	different	different	ADJ
fcis-6362	177	14	words	word	NOUN
fcis-6362	177	15	can	can	AUX
fcis-6362	177	16	lead	lead	VERB
fcis-6362	177	17	to	to	ADP
fcis-6362	177	18	huge	huge	ADJ
fcis-6362	177	19	differences	difference	NOUN
fcis-6362	177	20	in	in	ADP
fcis-6362	177	21	model	model	NOUN
fcis-6362	177	22	performance	performance	NOUN
fcis-6362	177	23	.	.	PUNCT
fcis-6362	178	1	table	table	NOUN
fcis-6362	178	2	4	4	NUM
fcis-6362	178	3	taken	take	VERB
fcis-6362	178	4	from	from	ADP
fcis-6362	178	5	the	the	DET
fcis-6362	178	6	work	work	NOUN
fcis-6362	178	7	of	of	ADP
fcis-6362	178	8	gao	gao	PROPN
fcis-6362	178	9	et	et	PROPN
fcis-6362	178	10	al	al	PROPN
fcis-6362	178	11	.	.	PROPN
fcis-6362	178	12	,	,	PUNCT
fcis-6362	178	13	illustrates	illustrate	VERB
fcis-6362	178	14	this	this	DET
fcis-6362	178	15	point	point	NOUN
fcis-6362	178	16	.	.	PUNCT
fcis-6362	179	1	it	it	PRON
fcis-6362	179	2	can	can	AUX
fcis-6362	179	3	be	be	AUX
fcis-6362	179	4	seen	see	VERB
fcis-6362	179	5	that	that	SCONJ
fcis-6362	179	6	relying	rely	VERB
fcis-6362	179	7	solely	solely	ADV
fcis-6362	179	8	on	on	ADP
fcis-6362	179	9	manual	manual	ADJ
fcis-6362	179	10	creation	creation	NOUN
fcis-6362	179	11	for	for	ADP
fcis-6362	179	12	both	both	DET
fcis-6362	179	13	templates	template	NOUN
fcis-6362	179	14	and	and	CCONJ
fcis-6362	179	15	answer	answer	NOUN
fcis-6362	179	16	spaces	space	NOUN
fcis-6362	179	17	is	be	AUX
fcis-6362	179	18	inefficient	inefficient	ADJ
fcis-6362	179	19	and	and	CCONJ
fcis-6362	179	20	unstable	unstable	ADJ
fcis-6362	179	21	.	.	PUNCT
fcis-6362	180	1	compared	compare	VERB
fcis-6362	180	2	to	to	ADP
fcis-6362	180	3	soft	soft	ADJ
fcis-6362	180	4	prompts	prompt	NOUN
fcis-6362	180	5	that	that	PRON
fcis-6362	180	6	lack	lack	VERB
fcis-6362	180	7	interpretability	interpretability	NOUN
fcis-6362	180	8	,	,	PUNCT
fcis-6362	180	9	most	most	ADJ
fcis-6362	180	10	tasks	task	NOUN
fcis-6362	180	11	are	be	AUX
fcis-6362	180	12	more	more	ADV
fcis-6362	180	13	inclined	inclined	ADJ
fcis-6362	180	14	to	to	PART
fcis-6362	180	15	select	select	VERB
fcis-6362	180	16	or	or	CCONJ
fcis-6362	180	17	generate	generate	VERB
fcis-6362	180	18	templates	template	NOUN
fcis-6362	180	19	and	and	CCONJ
fcis-6362	180	20	170	170	NUM
fcis-6362	180	21	answer	answer	NOUN
fcis-6362	180	22	spaces	space	VERB
fcis-6362	180	23	through	through	ADP
fcis-6362	180	24	algorithms	algorithm	NOUN
fcis-6362	180	25	.	.	PUNCT
fcis-6362	181	1	autoprompt	autoprompt	PROPN
fcis-6362	181	2	defines	define	VERB
fcis-6362	181	3	the	the	DET
fcis-6362	181	4	model	model	NOUN
fcis-6362	181	5	's	's	PART
fcis-6362	181	6	prediction	prediction	NOUN
fcis-6362	181	7	for	for	ADP
fcis-6362	181	8	label	label	NOUN
fcis-6362	181	9	𝑦	𝑦	NOUN
fcis-6362	181	10	as	as	ADP
fcis-6362	181	11	the	the	DET
fcis-6362	181	12	sum	sum	NOUN
fcis-6362	181	13	of	of	ADP
fcis-6362	181	14	the	the	DET
fcis-6362	181	15	probability	probability	NOUN
fcis-6362	181	16	outputs	output	NOUN
fcis-6362	181	17	of	of	ADP
fcis-6362	181	18	the	the	DET
fcis-6362	181	19	model	model	NOUN
fcis-6362	181	20	on	on	ADP
fcis-6362	181	21	all	all	DET
fcis-6362	181	22	candidate	candidate	NOUN
fcis-6362	181	23	words	word	NOUN
fcis-6362	181	24	𝑉𝑦	𝑉𝑦	NOUN
fcis-6362	181	25	:	:	PUNCT
fcis-6362	181	26	table	table	NOUN
fcis-6362	181	27	4	4	NUM
fcis-6362	181	28	.	.	PUNCT
fcis-6362	182	1	the	the	DET
fcis-6362	182	2	impact	impact	NOUN
fcis-6362	182	3	of	of	ADP
fcis-6362	182	4	templates	template	NOUN
fcis-6362	182	5	and	and	CCONJ
fcis-6362	182	6	label	label	NOUN
fcis-6362	182	7	words	word	NOUN
fcis-6362	182	8	on	on	ADP
fcis-6362	182	9	sst-2	sst-2	PUNCT
fcis-6362	182	10	dataset	dataset	NOUN
fcis-6362	182	11	template	template	NOUN
fcis-6362	182	12	label	label	NOUN
fcis-6362	182	13	words	word	NOUN
fcis-6362	182	14	accuracy(std	accuracy(std	NOUN
fcis-6362	182	15	)	)	PUNCT
fcis-6362	183	1	[	[	X
fcis-6362	183	2	𝑿	𝑿	X
fcis-6362	183	3	]	]	X
fcis-6362	183	4	it	it	PRON
fcis-6362	183	5	was	be	AUX
fcis-6362	183	6	[	[	X
fcis-6362	183	7	𝒀	𝒀	X
fcis-6362	183	8	]	]	X
fcis-6362	183	9	.	.	PUNCT
fcis-6362	184	1	great	great	ADJ
fcis-6362	184	2	/	/	SYM
fcis-6362	184	3	terrible	terrible	ADJ
fcis-6362	184	4	92.7	92.7	NUM
fcis-6362	184	5	(	(	PUNCT
fcis-6362	184	6	0.9	0.9	NUM
fcis-6362	184	7	)	)	PUNCT
fcis-6362	185	1	[	[	X
fcis-6362	185	2	𝑿	𝑿	X
fcis-6362	185	3	]	]	X
fcis-6362	185	4	it	it	PRON
fcis-6362	185	5	was	be	AUX
fcis-6362	185	6	[	[	X
fcis-6362	185	7	𝒀	𝒀	X
fcis-6362	185	8	]	]	X
fcis-6362	185	9	.	.	PUNCT
fcis-6362	186	1	good	good	ADJ
fcis-6362	186	2	/	/	SYM
fcis-6362	186	3	bad	bad	ADJ
fcis-6362	186	4	92.5	92.5	NUM
fcis-6362	186	5	(	(	PUNCT
fcis-6362	186	6	1.0	1.0	NUM
fcis-6362	186	7	)	)	PUNCT
fcis-6362	187	1	[	[	X
fcis-6362	187	2	𝑿	𝑿	X
fcis-6362	187	3	]	]	X
fcis-6362	187	4	it	it	PRON
fcis-6362	187	5	was	be	AUX
fcis-6362	187	6	[	[	X
fcis-6362	187	7	𝒀	𝒀	X
fcis-6362	187	8	]	]	X
fcis-6362	187	9	.	.	PUNCT
fcis-6362	188	1	cat	cat	NOUN
fcis-6362	188	2	/	/	SYM
fcis-6362	188	3	dog	dog	NOUN
fcis-6362	188	4	91.5	91.5	NUM
fcis-6362	188	5	(	(	PUNCT
fcis-6362	188	6	1.4	1.4	NUM
fcis-6362	188	7	)	)	PUNCT
fcis-6362	189	1	[	[	X
fcis-6362	189	2	𝑿	𝑿	X
fcis-6362	189	3	]	]	X
fcis-6362	189	4	it	it	PRON
fcis-6362	189	5	was	be	AUX
fcis-6362	189	6	[	[	X
fcis-6362	189	7	𝒀	𝒀	X
fcis-6362	189	8	]	]	X
fcis-6362	189	9	.	.	PUNCT
fcis-6362	190	1	dog	dog	NOUN
fcis-6362	190	2	/	/	SYM
fcis-6362	190	3	cat	cat	NOUN
fcis-6362	190	4	86.2	86.2	NUM
fcis-6362	190	5	(	(	PUNCT
fcis-6362	190	6	5.4	5.4	NUM
fcis-6362	190	7	)	)	PUNCT
fcis-6362	191	1	[	[	X
fcis-6362	191	2	𝑿	𝑿	X
fcis-6362	191	3	]	]	X
fcis-6362	191	4	it	it	PRON
fcis-6362	191	5	was	be	AUX
fcis-6362	191	6	[	[	X
fcis-6362	191	7	𝒀	𝒀	X
fcis-6362	191	8	]	]	X
fcis-6362	191	9	.	.	PUNCT
fcis-6362	192	1	terrible	terrible	ADJ
fcis-6362	192	2	/	/	SYM
fcis-6362	192	3	great	great	ADJ
fcis-6362	192	4	83.2	83.2	NUM
fcis-6362	192	5	(	(	PUNCT
fcis-6362	192	6	6.9	6.9	NUM
fcis-6362	192	7	)	)	PUNCT
fcis-6362	192	8	𝑝(𝑦|𝒙prompt	𝑝(𝑦|𝒙prompt	NOUN
fcis-6362	192	9	)	)	PUNCT
fcis-6362	192	10	=	=	SYM
fcis-6362	193	1	∑	∑	PUNCT
fcis-6362	193	2	𝑝𝑤∈𝒱𝑦	𝑝𝑤∈𝒱𝑦	X
fcis-6362	193	3	(	(	PUNCT
fcis-6362	193	4	[	[	X
fcis-6362	193	5	𝑦	𝑦	X
fcis-6362	193	6	]	]	X
fcis-6362	193	7	=	=	SYM
fcis-6362	193	8	𝑤|𝒙prompt	𝑤|𝒙prompt	NOUN
fcis-6362	193	9	)	)	PUNCT
fcis-6362	193	10	(	(	PUNCT
fcis-6362	193	11	1	1	X
fcis-6362	193	12	)	)	PUNCT
fcis-6362	193	13	when	when	SCONJ
fcis-6362	193	14	replacing	replace	VERB
fcis-6362	193	15	any	any	DET
fcis-6362	193	16	word	word	NOUN
fcis-6362	193	17	in	in	ADP
fcis-6362	193	18	𝑉𝑦	𝑉𝑦	PROPN
fcis-6362	193	19	,	,	PUNCT
fcis-6362	193	20	the	the	DET
fcis-6362	193	21	gradient	gradient	NOUN
fcis-6362	193	22	of	of	ADP
fcis-6362	193	23	the	the	DET
fcis-6362	193	24	model	model	NOUN
fcis-6362	193	25	's	's	PART
fcis-6362	193	26	output	output	NOUN
fcis-6362	193	27	p	p	NOUN
fcis-6362	193	28	changes	change	NOUN
fcis-6362	193	29	significantly	significantly	ADV
fcis-6362	193	30	,	,	PUNCT
fcis-6362	193	31	indicating	indicate	VERB
fcis-6362	193	32	a	a	DET
fcis-6362	193	33	strong	strong	ADJ
fcis-6362	193	34	correlation	correlation	NOUN
fcis-6362	193	35	between	between	ADP
fcis-6362	193	36	the	the	DET
fcis-6362	193	37	replaced	replace	VERB
fcis-6362	193	38	word	word	NOUN
fcis-6362	193	39	and	and	CCONJ
fcis-6362	193	40	label	label	NOUN
fcis-6362	193	41	𝑦	𝑦	NOUN
fcis-6362	193	42	,	,	PUNCT
fcis-6362	193	43	thus	thus	ADV
fcis-6362	193	44	it	it	PRON
fcis-6362	193	45	can	can	AUX
fcis-6362	193	46	be	be	AUX
fcis-6362	193	47	included	include	VERB
fcis-6362	193	48	in	in	ADP
fcis-6362	193	49	the	the	DET
fcis-6362	193	50	answer	answer	NOUN
fcis-6362	193	51	space	space	NOUN
fcis-6362	193	52	.	.	PUNCT
fcis-6362	194	1	𝒱cand	𝒱cand	NOUN
fcis-6362	194	2	=	=	PUNCT
fcis-6362	194	3	top	top	ADJ
fcis-6362	194	4	−	−	PROPN
fcis-6362	194	5	𝑘	𝑘	ADP
fcis-6362	194	6	𝑤∈𝒱	𝑤∈𝒱	PROPN
fcis-6362	195	1	[	[	X
fcis-6362	195	2	𝒘in	𝒘in	PROPN
fcis-6362	195	3	𝑇	𝑇	PROPN
fcis-6362	195	4	∇log	∇log	PROPN
fcis-6362	195	5	𝑝	𝑝	PROPN
fcis-6362	195	6	(	(	PUNCT
fcis-6362	195	7	𝑦	𝑦	NOUN
fcis-6362	195	8	|	|	ADV
fcis-6362	195	9	𝒙prompt	𝒙prompt	ADJ
fcis-6362	195	10	)	)	PUNCT
fcis-6362	195	11	]	]	PUNCT
fcis-6362	195	12	(	(	PUNCT
fcis-6362	195	13	2	2	X
fcis-6362	195	14	)	)	PUNCT
fcis-6362	195	15	gao	gao	PROPN
fcis-6362	195	16	et	et	PROPN
fcis-6362	195	17	al	al	PROPN
fcis-6362	195	18	.	.	PROPN
fcis-6362	195	19	proposed	propose	VERB
fcis-6362	195	20	a	a	DET
fcis-6362	195	21	method	method	NOUN
fcis-6362	195	22	for	for	ADP
fcis-6362	195	23	automatically	automatically	ADV
fcis-6362	195	24	searching	search	VERB
fcis-6362	195	25	templates	template	NOUN
fcis-6362	195	26	,	,	PUNCT
fcis-6362	195	27	which	which	PRON
fcis-6362	195	28	involves	involve	VERB
fcis-6362	195	29	adding	add	VERB
fcis-6362	195	30	placeholder	placeholder	NOUN
fcis-6362	195	31	tokens	token	NOUN
fcis-6362	195	32	around	around	ADP
fcis-6362	195	33	the	the	DET
fcis-6362	195	34	target	target	NOUN
fcis-6362	195	35	words	word	NOUN
fcis-6362	195	36	and	and	CCONJ
fcis-6362	195	37	filling	fill	VERB
fcis-6362	195	38	these	these	DET
fcis-6362	195	39	tokens	token	NOUN
fcis-6362	195	40	using	use	VERB
fcis-6362	195	41	the	the	DET
fcis-6362	195	42	t5	t5	PROPN
fcis-6362	195	43	model[22	model[22	NOUN
fcis-6362	195	44	]	]	PUNCT
fcis-6362	195	45	to	to	PART
fcis-6362	195	46	generate	generate	VERB
fcis-6362	195	47	a	a	DET
fcis-6362	195	48	set	set	NOUN
fcis-6362	195	49	of	of	ADP
fcis-6362	195	50	template	template	NOUN
fcis-6362	195	51	candidates	candidate	NOUN
fcis-6362	195	52	.	.	PUNCT
fcis-6362	196	1	then	then	ADV
fcis-6362	196	2	,	,	PUNCT
fcis-6362	196	3	the	the	DET
fcis-6362	196	4	performance	performance	NOUN
fcis-6362	196	5	of	of	ADP
fcis-6362	196	6	these	these	DET
fcis-6362	196	7	templates	template	NOUN
fcis-6362	196	8	on	on	ADP
fcis-6362	196	9	the	the	DET
fcis-6362	196	10	training	training	NOUN
fcis-6362	196	11	set	set	NOUN
fcis-6362	196	12	is	be	AUX
fcis-6362	196	13	calculated	calculate	VERB
fcis-6362	196	14	by	by	ADP
fcis-6362	196	15	selecting	select	VERB
fcis-6362	196	16	the	the	DET
fcis-6362	196	17	templates	template	NOUN
fcis-6362	196	18	with	with	ADP
fcis-6362	196	19	the	the	DET
fcis-6362	196	20	highest	high	ADJ
fcis-6362	196	21	sum	sum	NOUN
fcis-6362	196	22	of	of	ADP
fcis-6362	196	23	output	output	NOUN
fcis-6362	196	24	probabilities	probability	NOUN
fcis-6362	196	25	across	across	ADP
fcis-6362	196	26	all	all	DET
fcis-6362	196	27	samples	sample	NOUN
fcis-6362	196	28	.	.	PUNCT
fcis-6362	197	1	∑	∑	PUNCT
fcis-6362	197	2	∑	∑	PUNCT
fcis-6362	197	3	𝑃t5(𝑥in,𝑦)∈𝒟rain	𝑃t5(𝑥in,𝑦)∈𝒟rain	PROPN
fcis-6362	197	4	|𝑇|	|𝑇|	PROPN
fcis-6362	197	5	𝑗=1	𝑗=1	PROPN
fcis-6362	197	6	big(𝑡𝑗	big(𝑡𝑗	NOUN
fcis-6362	197	7	∣	∣	ADJ
fcis-6362	197	8	𝑡1	𝑡1	NOUN
fcis-6362	197	9	,	,	PUNCT
fcis-6362	197	10	.	.	PUNCT
fcis-6362	197	11	.	.	PUNCT
fcis-6362	198	1	.	.	PUNCT
fcis-6362	199	1	,	,	PUNCT
fcis-6362	199	2	𝑡𝑗−1	𝑡𝑗−1	PROPN
fcis-6362	199	3	,	,	PUNCT
fcis-6362	199	4	𝒯g(𝑥in	𝒯g(𝑥in	ADJ
fcis-6362	199	5	,	,	PUNCT
fcis-6362	199	6	𝑦	𝑦	NOUN
fcis-6362	199	7	)	)	PUNCT
fcis-6362	199	8	)	)	PUNCT
fcis-6362	199	9	(	(	PUNCT
fcis-6362	199	10	3	3	X
fcis-6362	199	11	)	)	PUNCT
fcis-6362	199	12	another	another	DET
fcis-6362	199	13	way	way	NOUN
fcis-6362	199	14	to	to	PART
fcis-6362	199	15	enhance	enhance	VERB
fcis-6362	199	16	the	the	DET
fcis-6362	199	17	modeling	modeling	NOUN
fcis-6362	199	18	capability	capability	NOUN
fcis-6362	199	19	proposed	propose	VERB
fcis-6362	199	20	by	by	ADP
fcis-6362	199	21	gao	gao	PROPN
fcis-6362	199	22	et	et	PROPN
fcis-6362	199	23	al	al	PROPN
fcis-6362	199	24	.	.	PROPN
fcis-6362	199	25	is	be	AUX
fcis-6362	199	26	to	to	PART
fcis-6362	199	27	use	use	VERB
fcis-6362	199	28	demonstrations	demonstration	NOUN
fcis-6362	199	29	to	to	PART
fcis-6362	199	30	indicate	indicate	VERB
fcis-6362	199	31	to	to	ADP
fcis-6362	199	32	the	the	DET
fcis-6362	199	33	model	model	NOUN
fcis-6362	199	34	what	what	PRON
fcis-6362	199	35	it	it	PRON
fcis-6362	199	36	should	should	AUX
fcis-6362	199	37	learn	learn	VERB
fcis-6362	199	38	.	.	PUNCT
fcis-6362	200	1	the	the	DET
fcis-6362	200	2	method	method	NOUN
fcis-6362	200	3	is	be	AUX
fcis-6362	200	4	to	to	PART
fcis-6362	200	5	randomly	randomly	VERB
fcis-6362	200	6	sample	sample	NOUN
fcis-6362	200	7	examples	example	NOUN
fcis-6362	200	8	and	and	CCONJ
fcis-6362	200	9	concatenate	concatenate	VERB
fcis-6362	200	10	them	they	PRON
fcis-6362	200	11	during	during	ADP
fcis-6362	200	12	the	the	DET
fcis-6362	200	13	training	training	NOUN
fcis-6362	200	14	process	process	NOUN
fcis-6362	200	15	.	.	PUNCT
fcis-6362	201	1	figure	figure	NOUN
fcis-6362	201	2	1	1	NUM
fcis-6362	201	3	shows	show	VERB
fcis-6362	201	4	this	this	DET
fcis-6362	201	5	process	process	NOUN
fcis-6362	201	6	.	.	PUNCT
fcis-6362	202	1	figure	figure	NOUN
fcis-6362	202	2	1	1	NUM
fcis-6362	202	3	.	.	PUNCT
fcis-6362	203	1	prompt	prompt	NOUN
fcis-6362	203	2	-	-	PUNCT
fcis-6362	203	3	based	base	VERB
fcis-6362	203	4	fine	fine	ADV
fcis-6362	203	5	-	-	PUNCT
fcis-6362	203	6	tuning	tuning	NOUN
fcis-6362	203	7	with	with	ADP
fcis-6362	203	8	demonstrations	demonstration	NOUN
fcis-6362	203	9	in	in	ADP
fcis-6362	203	10	our	our	PRON
fcis-6362	203	11	work	work	NOUN
fcis-6362	203	12	,	,	PUNCT
fcis-6362	203	13	we	we	PRON
fcis-6362	203	14	use	use	VERB
fcis-6362	203	15	a	a	DET
fcis-6362	203	16	method	method	NOUN
fcis-6362	203	17	opposite	opposite	NOUN
fcis-6362	203	18	to	to	PART
fcis-6362	203	19	prompt	prompt	VERB
fcis-6362	203	20	learning	learn	VERB
fcis-6362	203	21	to	to	PART
fcis-6362	203	22	enhance	enhance	VERB
fcis-6362	203	23	the	the	DET
fcis-6362	203	24	model	model	NOUN
fcis-6362	203	25	's	's	PART
fcis-6362	203	26	ability	ability	NOUN
fcis-6362	203	27	.	.	PUNCT
fcis-6362	204	1	that	that	PRON
fcis-6362	204	2	is	is	ADV
fcis-6362	204	3	,	,	PUNCT
fcis-6362	204	4	we	we	PRON
fcis-6362	204	5	keep	keep	VERB
fcis-6362	204	6	the	the	DET
fcis-6362	204	7	target	target	NOUN
fcis-6362	204	8	words	word	NOUN
fcis-6362	204	9	in	in	ADP
fcis-6362	204	10	the	the	DET
fcis-6362	204	11	template	template	NOUN
fcis-6362	204	12	and	and	CCONJ
fcis-6362	204	13	randomly	randomly	ADV
fcis-6362	204	14	mask	mask	VERB
fcis-6362	204	15	the	the	DET
fcis-6362	204	16	tokens	token	NOUN
fcis-6362	204	17	of	of	ADP
fcis-6362	204	18	the	the	DET
fcis-6362	204	19	original	original	ADJ
fcis-6362	204	20	corpus	corpus	NOUN
fcis-6362	204	21	,	,	PUNCT
fcis-6362	204	22	and	and	CCONJ
fcis-6362	204	23	let	let	VERB
fcis-6362	204	24	the	the	DET
fcis-6362	204	25	model	model	NOUN
fcis-6362	204	26	predict	predict	VERB
fcis-6362	204	27	the	the	DET
fcis-6362	204	28	masked	masked	ADJ
fcis-6362	204	29	tokens	token	NOUN
fcis-6362	204	30	.	.	PUNCT
fcis-6362	205	1	from	from	ADP
fcis-6362	205	2	the	the	DET
fcis-6362	205	3	perspective	perspective	NOUN
fcis-6362	205	4	of	of	ADP
fcis-6362	205	5	feature	feature	NOUN
fcis-6362	205	6	engineering	engineering	NOUN
fcis-6362	205	7	,	,	PUNCT
fcis-6362	205	8	the	the	DET
fcis-6362	205	9	model	model	NOUN
fcis-6362	205	10	's	's	PART
fcis-6362	205	11	prediction	prediction	NOUN
fcis-6362	205	12	ability	ability	NOUN
fcis-6362	205	13	comes	come	VERB
fcis-6362	205	14	from	from	ADP
fcis-6362	205	15	extracting	extract	VERB
fcis-6362	205	16	features	feature	NOUN
fcis-6362	205	17	from	from	ADP
fcis-6362	205	18	the	the	DET
fcis-6362	205	19	samples	sample	NOUN
fcis-6362	205	20	,	,	PUNCT
fcis-6362	205	21	that	that	ADV
fcis-6362	205	22	is	is	ADV
fcis-6362	205	23	,	,	PUNCT
fcis-6362	205	24	the	the	DET
fcis-6362	205	25	model	model	NOUN
fcis-6362	205	26	establishes	establish	VERB
fcis-6362	205	27	a	a	DET
fcis-6362	205	28	mapping	mapping	NOUN
fcis-6362	205	29	relationship	relationship	NOUN
fcis-6362	205	30	between	between	ADP
fcis-6362	205	31	the	the	DET
fcis-6362	205	32	samples	sample	NOUN
fcis-6362	205	33	and	and	CCONJ
fcis-6362	205	34	the	the	DET
fcis-6362	205	35	features	feature	NOUN
fcis-6362	205	36	.	.	PUNCT
fcis-6362	206	1	if	if	SCONJ
fcis-6362	206	2	samples	sample	NOUN
fcis-6362	206	3	can	can	AUX
fcis-6362	206	4	be	be	AUX
fcis-6362	206	5	mapped	map	VERB
fcis-6362	206	6	to	to	ADP
fcis-6362	206	7	features	feature	NOUN
fcis-6362	206	8	,	,	PUNCT
fcis-6362	206	9	then	then	ADV
fcis-6362	206	10	features	feature	NOUN
fcis-6362	206	11	can	can	AUX
fcis-6362	206	12	also	also	ADV
fcis-6362	206	13	be	be	AUX
fcis-6362	206	14	mapped	map	VERB
fcis-6362	206	15	to	to	ADP
fcis-6362	206	16	samples	sample	NOUN
fcis-6362	206	17	.	.	PUNCT
fcis-6362	207	1	for	for	ADP
fcis-6362	207	2	example	example	NOUN
fcis-6362	207	3	,	,	PUNCT
fcis-6362	207	4	variational	variational	ADJ
fcis-6362	207	5	encoder	encoder	NOUN
fcis-6362	207	6	(	(	PUNCT
fcis-6362	207	7	vae)[23	vae)[23	PROPN
fcis-6362	207	8	]	]	PUNCT
fcis-6362	207	9	also	also	ADV
fcis-6362	207	10	known	know	VERB
fcis-6362	207	11	as	as	ADP
fcis-6362	207	12	a	a	DET
fcis-6362	207	13	generative	generative	ADJ
fcis-6362	207	14	model	model	NOUN
fcis-6362	207	15	,	,	PUNCT
fcis-6362	207	16	can	can	AUX
fcis-6362	207	17	map	map	VERB
fcis-6362	207	18	high	high	ADJ
fcis-6362	207	19	-	-	PUNCT
fcis-6362	207	20	dimensional	dimensional	ADJ
fcis-6362	207	21	data	datum	NOUN
fcis-6362	207	22	such	such	ADJ
fcis-6362	207	23	as	as	ADP
fcis-6362	207	24	images	image	NOUN
fcis-6362	207	25	and	and	CCONJ
fcis-6362	207	26	audio	audio	NOUN
fcis-6362	207	27	into	into	ADP
fcis-6362	207	28	a	a	DET
fcis-6362	207	29	low	low	ADJ
fcis-6362	207	30	-	-	PUNCT
fcis-6362	207	31	dimensional	dimensional	ADJ
fcis-6362	207	32	latent	latent	NOUN
fcis-6362	207	33	space	space	NOUN
fcis-6362	207	34	and	and	CCONJ
fcis-6362	207	35	generate	generate	VERB
fcis-6362	207	36	new	new	ADJ
fcis-6362	207	37	data	datum	NOUN
fcis-6362	207	38	from	from	ADP
fcis-6362	207	39	it	it	PRON
fcis-6362	207	40	.	.	PUNCT
fcis-6362	208	1	a	a	DET
fcis-6362	208	2	more	more	ADV
fcis-6362	208	3	intuitive	intuitive	ADJ
fcis-6362	208	4	example	example	NOUN
fcis-6362	208	5	is	be	AUX
fcis-6362	208	6	that	that	SCONJ
fcis-6362	208	7	humans	human	NOUN
fcis-6362	208	8	can	can	AUX
fcis-6362	208	9	infer	infer	VERB
fcis-6362	208	10	from	from	ADP
fcis-6362	208	11	the	the	DET
fcis-6362	208	12	template	template	NOUN
fcis-6362	208	13	"	"	PUNCT
fcis-6362	208	14	i	i	PRON
fcis-6362	208	15	love	love	VERB
fcis-6362	208	16	this	this	DET
fcis-6362	208	17	movie	movie	NOUN
fcis-6362	208	18	.	.	PUNCT
fcis-6362	209	1	this	this	DET
fcis-6362	209	2	movie	movie	NOUN
fcis-6362	209	3	is	be	AUX
fcis-6362	209	4	_	_	PRON
fcis-6362	209	5	"	"	PUNCT
fcis-6362	209	6	that	that	SCONJ
fcis-6362	209	7	the	the	DET
fcis-6362	209	8	missing	missing	ADJ
fcis-6362	209	9	word	word	NOUN
fcis-6362	209	10	should	should	AUX
fcis-6362	209	11	be	be	AUX
fcis-6362	209	12	"	"	PUNCT
fcis-6362	209	13	great	great	ADJ
fcis-6362	209	14	"	"	PUNCT
fcis-6362	209	15	,	,	PUNCT
fcis-6362	209	16	and	and	CCONJ
fcis-6362	209	17	also	also	ADV
fcis-6362	209	18	infer	infer	VERB
fcis-6362	209	19	from	from	ADP
fcis-6362	209	20	the	the	DET
fcis-6362	209	21	template	template	NOUN
fcis-6362	209	22	"	"	PUNCT
fcis-6362	209	23	i	i	PRON
fcis-6362	209	24	_	_	NOUN
fcis-6362	209	25	this	this	DET
fcis-6362	209	26	movie	movie	NOUN
fcis-6362	209	27	.	.	PUNCT
fcis-6362	210	1	this	this	DET
fcis-6362	210	2	movie	movie	NOUN
fcis-6362	210	3	is	be	AUX
fcis-6362	210	4	great	great	ADJ
fcis-6362	210	5	.	.	PUNCT
fcis-6362	210	6	"	"	PUNCT
fcis-6362	211	1	that	that	SCONJ
fcis-6362	211	2	the	the	DET
fcis-6362	211	3	missing	missing	ADJ
fcis-6362	211	4	word	word	NOUN
fcis-6362	211	5	should	should	AUX
fcis-6362	211	6	be	be	AUX
fcis-6362	211	7	"	"	PUNCT
fcis-6362	211	8	love	love	NOUN
fcis-6362	211	9	"	"	PUNCT
fcis-6362	211	10	.	.	PUNCT
fcis-6362	212	1	therefore	therefore	ADV
fcis-6362	212	2	,	,	PUNCT
fcis-6362	212	3	these	these	DET
fcis-6362	212	4	two	two	NUM
fcis-6362	212	5	tasks	task	NOUN
fcis-6362	212	6	mutually	mutually	ADV
fcis-6362	212	7	reinforce	reinforce	VERB
fcis-6362	212	8	the	the	DET
fcis-6362	212	9	model	model	NOUN
fcis-6362	212	10	's	's	PART
fcis-6362	212	11	ability	ability	NOUN
fcis-6362	212	12	in	in	ADP
fcis-6362	212	13	sentiment	sentiment	NOUN
fcis-6362	212	14	analysis	analysis	NOUN
fcis-6362	212	15	.	.	PUNCT
fcis-6362	213	1	in	in	ADP
fcis-6362	213	2	fact	fact	NOUN
fcis-6362	213	3	,	,	PUNCT
fcis-6362	213	4	the	the	DET
fcis-6362	213	5	training	training	NOUN
fcis-6362	213	6	methods	method	NOUN
fcis-6362	213	7	for	for	ADP
fcis-6362	213	8	modern	modern	ADJ
fcis-6362	213	9	natural	natural	ADJ
fcis-6362	213	10	language	language	NOUN
fcis-6362	213	11	processing	processing	NOUN
fcis-6362	213	12	models	model	NOUN
fcis-6362	213	13	are	be	AUX
fcis-6362	213	14	becoming	become	VERB
fcis-6362	213	15	more	more	ADV
fcis-6362	213	16	and	and	CCONJ
fcis-6362	213	17	more	more	ADV
fcis-6362	213	18	similar	similar	ADJ
fcis-6362	213	19	to	to	ADP
fcis-6362	213	20	teaching	teach	VERB
fcis-6362	213	21	a	a	DET
fcis-6362	213	22	child	child	NOUN
fcis-6362	213	23	knowledge	knowledge	NOUN
fcis-6362	213	24	.	.	PUNCT
fcis-6362	214	1	the	the	DET
fcis-6362	214	2	"	"	PUNCT
fcis-6362	214	3	mask	mask	NOUN
fcis-6362	214	4	"	"	PUNCT
fcis-6362	214	5	approach	approach	NOUN
fcis-6362	214	6	used	use	VERB
fcis-6362	214	7	in	in	ADP
fcis-6362	214	8	large	large	ADJ
fcis-6362	214	9	-	-	PUNCT
fcis-6362	214	10	scale	scale	NOUN
fcis-6362	214	11	pre	pre	ADJ
fcis-6362	214	12	-	-	ADJ
fcis-6362	214	13	training	training	ADJ
fcis-6362	214	14	models	model	NOUN
fcis-6362	214	15	actually	actually	ADV
fcis-6362	214	16	originated	originate	VERB
fcis-6362	214	17	from	from	ADP
fcis-6362	214	18	the	the	DET
fcis-6362	214	19	common	common	ADJ
fcis-6362	214	20	practice	practice	NOUN
fcis-6362	214	21	of	of	ADP
fcis-6362	214	22	fill	fill	NOUN
fcis-6362	214	23	-	-	PUNCT
fcis-6362	214	24	in	in	ADP
fcis-6362	214	25	-	-	PUNCT
fcis-6362	214	26	the	the	DET
fcis-6362	214	27	-	-	PUNCT
fcis-6362	214	28	blank	blank	ADJ
fcis-6362	214	29	questions	question	NOUN
fcis-6362	214	30	in	in	ADP
fcis-6362	214	31	exams	exam	NOUN
fcis-6362	214	32	.	.	PUNCT
fcis-6362	215	1	another	another	DET
fcis-6362	215	2	term	term	NOUN
fcis-6362	215	3	for	for	ADP
fcis-6362	215	4	the	the	DET
fcis-6362	215	5	demonstrations	demonstration	NOUN
fcis-6362	215	6	approach	approach	NOUN
fcis-6362	215	7	proposed	propose	VERB
fcis-6362	215	8	by	by	ADP
fcis-6362	215	9	gao	gao	PROPN
fcis-6362	215	10	et	et	PROPN
fcis-6362	215	11	al	al	PROPN
fcis-6362	215	12	is	be	AUX
fcis-6362	215	13	"	"	PUNCT
fcis-6362	215	14	example	example	NOUN
fcis-6362	215	15	questions	question	NOUN
fcis-6362	215	16	"	"	PUNCT
fcis-6362	215	17	and	and	CCONJ
fcis-6362	215	18	"	"	PUNCT
fcis-6362	215	19	real	real	ADJ
fcis-6362	215	20	questions	question	NOUN
fcis-6362	215	21	"	"	PUNCT
fcis-6362	215	22	.	.	PUNCT
fcis-6362	216	1	therefore	therefore	ADV
fcis-6362	216	2	,	,	PUNCT
fcis-6362	216	3	the	the	DET
fcis-6362	216	4	bidirectional	bidirectional	ADJ
fcis-6362	216	5	prompt	prompt	ADJ
fcis-6362	216	6	learning	learning	NOUN
fcis-6362	216	7	method	method	NOUN
fcis-6362	216	8	we	we	PRON
fcis-6362	216	9	propose	propose	VERB
fcis-6362	216	10	is	be	AUX
fcis-6362	216	11	scientifically	scientifically	ADV
fcis-6362	216	12	effective	effective	ADJ
fcis-6362	216	13	and	and	CCONJ
fcis-6362	216	14	in	in	ADP
fcis-6362	216	15	line	line	NOUN
fcis-6362	216	16	with	with	ADP
fcis-6362	216	17	human	human	ADJ
fcis-6362	216	18	intuition	intuition	NOUN
fcis-6362	216	19	.	.	PUNCT
fcis-6362	217	1	4	4	X
fcis-6362	217	2	.	.	X
fcis-6362	217	3	experiment	experiment	NOUN
fcis-6362	217	4	we	we	PRON
fcis-6362	217	5	validate	validate	VERB
fcis-6362	217	6	our	our	PRON
fcis-6362	217	7	method	method	NOUN
fcis-6362	217	8	on	on	ADP
fcis-6362	217	9	four	four	NUM
fcis-6362	217	10	natural	natural	ADJ
fcis-6362	217	11	language	language	NOUN
fcis-6362	217	12	classification	classification	NOUN
fcis-6362	217	13	datasets	dataset	NOUN
fcis-6362	217	14	.	.	PUNCT
fcis-6362	218	1	4.1	4.1	NUM
fcis-6362	218	2	.	.	PUNCT
fcis-6362	219	1	datasets	dataset	NOUN
fcis-6362	219	2	ag	ag	PROPN
fcis-6362	219	3	’s	’s	PART
fcis-6362	219	4	news	news	NOUN
fcis-6362	219	5	[	[	X
fcis-6362	219	6	24	24	NUM
fcis-6362	219	7	]	]	PUNCT
fcis-6362	219	8	is	be	AUX
fcis-6362	219	9	a	a	DET
fcis-6362	219	10	widely	widely	ADV
fcis-6362	219	11	used	use	VERB
fcis-6362	219	12	text	text	NOUN
fcis-6362	219	13	classification	classification	NOUN
fcis-6362	219	14	dataset	dataset	NOUN
fcis-6362	219	15	that	that	PRON
fcis-6362	219	16	includes	include	VERB
fcis-6362	219	17	news	news	NOUN
fcis-6362	219	18	articles	article	NOUN
fcis-6362	219	19	from	from	ADP
fcis-6362	219	20	four	four	NUM
fcis-6362	219	21	different	different	ADJ
fcis-6362	219	22	topics	topic	NOUN
fcis-6362	219	23	sports	sport	NOUN
fcis-6362	219	24	,	,	PUNCT
fcis-6362	219	25	technology	technology	NOUN
fcis-6362	219	26	,	,	PUNCT
fcis-6362	219	27	business	business	NOUN
fcis-6362	219	28	,	,	PUNCT
fcis-6362	219	29	and	and	CCONJ
fcis-6362	219	30	health	health	NOUN
fcis-6362	219	31	.	.	PUNCT
fcis-6362	220	1	the	the	DET
fcis-6362	220	2	dataset	dataset	NOUN
fcis-6362	220	3	contains	contain	VERB
fcis-6362	220	4	120,000	120,000	NUM
fcis-6362	220	5	news	news	NOUN
fcis-6362	220	6	articles	article	NOUN
fcis-6362	220	7	,	,	PUNCT
fcis-6362	220	8	with	with	ADP
fcis-6362	220	9	30,000	30,000	NUM
fcis-6362	220	10	articles	article	NOUN
fcis-6362	220	11	for	for	ADP
fcis-6362	220	12	each	each	DET
fcis-6362	220	13	topic	topic	NOUN
fcis-6362	220	14	.	.	PUNCT
fcis-6362	221	1	each	each	DET
fcis-6362	221	2	article	article	NOUN
fcis-6362	221	3	includes	include	VERB
fcis-6362	221	4	a	a	DET
fcis-6362	221	5	title	title	NOUN
fcis-6362	221	6	and	and	CCONJ
fcis-6362	221	7	a	a	DET
fcis-6362	221	8	description	description	NOUN
fcis-6362	221	9	,	,	PUNCT
fcis-6362	221	10	as	as	ADV
fcis-6362	221	11	well	well	ADV
fcis-6362	221	12	as	as	ADP
fcis-6362	221	13	a	a	DET
fcis-6362	221	14	numeric	numeric	ADJ
fcis-6362	221	15	representation	representation	NOUN
fcis-6362	221	16	of	of	ADP
fcis-6362	221	17	the	the	DET
fcis-6362	221	18	topic	topic	NOUN
fcis-6362	221	19	category	category	NOUN
fcis-6362	221	20	.	.	PUNCT
fcis-6362	222	1	yahoo	yahoo	PROPN
fcis-6362	222	2	is	be	AUX
fcis-6362	222	3	a	a	DET
fcis-6362	222	4	widely	widely	ADV
fcis-6362	222	5	used	use	VERB
fcis-6362	222	6	dataset	dataset	NOUN
fcis-6362	222	7	for	for	ADP
fcis-6362	222	8	natural	natural	ADJ
fcis-6362	222	9	language	language	NOUN
fcis-6362	222	10	processing	processing	NOUN
fcis-6362	222	11	and	and	CCONJ
fcis-6362	222	12	text	text	NOUN
fcis-6362	222	13	classification	classification	NOUN
fcis-6362	222	14	tasks	task	NOUN
fcis-6362	222	15	.	.	PUNCT
fcis-6362	223	1	provided	provide	VERB
fcis-6362	223	2	by	by	ADP
fcis-6362	223	3	yahoo	yahoo	PROPN
fcis-6362	223	4	research	research	NOUN
fcis-6362	223	5	,	,	PUNCT
fcis-6362	223	6	it	it	PRON
fcis-6362	223	7	contains	contain	VERB
fcis-6362	223	8	all	all	DET
fcis-6362	223	9	the	the	DET
fcis-6362	223	10	news	news	NOUN
fcis-6362	223	11	articles	article	NOUN
fcis-6362	223	12	collected	collect	VERB
fcis-6362	223	13	from	from	ADP
fcis-6362	223	14	yahoo	yahoo	PROPN
fcis-6362	223	15	news	news	PROPN
fcis-6362	223	16	,	,	PUNCT
fcis-6362	223	17	covering	cover	VERB
fcis-6362	223	18	various	various	ADJ
fcis-6362	223	19	topics	topic	NOUN
fcis-6362	223	20	such	such	ADJ
fcis-6362	223	21	as	as	ADP
fcis-6362	223	22	sports	sport	NOUN
fcis-6362	223	23	,	,	PUNCT
fcis-6362	223	24	politics	politic	NOUN
fcis-6362	223	25	,	,	PUNCT
fcis-6362	223	26	entertainment	entertainment	NOUN
fcis-6362	223	27	,	,	PUNCT
fcis-6362	223	28	and	and	CCONJ
fcis-6362	223	29	more	more	ADJ
fcis-6362	223	30	.	.	PUNCT
fcis-6362	224	1	each	each	DET
fcis-6362	224	2	article	article	NOUN
fcis-6362	224	3	in	in	ADP
fcis-6362	224	4	the	the	DET
fcis-6362	224	5	dataset	dataset	NOUN
fcis-6362	224	6	includes	include	VERB
fcis-6362	224	7	a	a	DET
fcis-6362	224	8	news	news	NOUN
fcis-6362	224	9	headline	headline	NOUN
fcis-6362	224	10	,	,	PUNCT
fcis-6362	224	11	description	description	NOUN
fcis-6362	224	12	,	,	PUNCT
fcis-6362	224	13	and	and	CCONJ
fcis-6362	224	14	full	full	ADJ
fcis-6362	224	15	text	text	NOUN
fcis-6362	224	16	,	,	PUNCT
fcis-6362	224	17	as	as	ADV
fcis-6362	224	18	well	well	ADV
fcis-6362	224	19	as	as	ADP
fcis-6362	224	20	a	a	DET
fcis-6362	224	21	corresponding	corresponding	ADJ
fcis-6362	224	22	topic	topic	NOUN
fcis-6362	224	23	label	label	NOUN
fcis-6362	224	24	.	.	PUNCT
fcis-6362	225	1	with	with	ADP
fcis-6362	225	2	around	around	ADP
fcis-6362	225	3	1,000,000	1,000,000	NUM
fcis-6362	225	4	articles	article	NOUN
fcis-6362	225	5	,	,	PUNCT
fcis-6362	225	6	this	this	DET
fcis-6362	225	7	dataset	dataset	NOUN
fcis-6362	225	8	is	be	AUX
fcis-6362	225	9	very	very	ADV
fcis-6362	225	10	large	large	ADJ
fcis-6362	225	11	and	and	CCONJ
fcis-6362	225	12	suitable	suitable	ADJ
fcis-6362	225	13	for	for	ADP
fcis-6362	225	14	training	training	NOUN
fcis-6362	225	15	and	and	CCONJ
fcis-6362	225	16	testing	test	VERB
fcis-6362	225	17	various	various	ADJ
fcis-6362	225	18	natural	natural	ADJ
fcis-6362	225	19	language	language	NOUN
fcis-6362	225	20	processing	processing	NOUN
fcis-6362	225	21	algorithms	algorithm	NOUN
fcis-6362	225	22	and	and	CCONJ
fcis-6362	225	23	models	model	NOUN
fcis-6362	225	24	.	.	PUNCT
fcis-6362	226	1	imdb	imdb	PROPN
fcis-6362	226	2	(	(	PUNCT
fcis-6362	226	3	internet	internet	NOUN
fcis-6362	226	4	movie	movie	NOUN
fcis-6362	226	5	database	database	NOUN
fcis-6362	226	6	)	)	PUNCT
fcis-6362	226	7	is	be	AUX
fcis-6362	226	8	an	an	DET
fcis-6362	226	9	online	online	ADJ
fcis-6362	226	10	database	database	NOUN
fcis-6362	226	11	of	of	ADP
fcis-6362	226	12	movies	movie	NOUN
fcis-6362	226	13	and	and	CCONJ
fcis-6362	226	14	television	television	NOUN
fcis-6362	226	15	shows	show	NOUN
fcis-6362	226	16	that	that	PRON
fcis-6362	226	17	includes	include	VERB
fcis-6362	226	18	the	the	DET
fcis-6362	226	19	world	world	NOUN
fcis-6362	226	20	's	's	PART
fcis-6362	226	21	widest	wide	ADJ
fcis-6362	226	22	range	range	NOUN
fcis-6362	226	23	of	of	ADP
fcis-6362	226	24	film	film	NOUN
fcis-6362	226	25	and	and	CCONJ
fcis-6362	226	26	television	television	NOUN
fcis-6362	226	27	information	information	NOUN
fcis-6362	226	28	,	,	PUNCT
fcis-6362	226	29	including	include	VERB
fcis-6362	226	30	movies	movie	NOUN
fcis-6362	226	31	,	,	PUNCT
fcis-6362	226	32	tv	tv	NOUN
fcis-6362	226	33	shows	show	NOUN
fcis-6362	226	34	,	,	PUNCT
fcis-6362	226	35	documentaries	documentary	NOUN
fcis-6362	226	36	,	,	PUNCT
fcis-6362	226	37	short	short	ADJ
fcis-6362	226	38	films	film	NOUN
fcis-6362	226	39	,	,	PUNCT
fcis-6362	226	40	made	make	VERB
fcis-6362	226	41	-	-	PUNCT
fcis-6362	226	42	for	for	ADP
fcis-6362	226	43	-	-	PUNCT
fcis-6362	226	44	tv	tv	NOUN
fcis-6362	226	45	movies	movie	NOUN
fcis-6362	226	46	,	,	PUNCT
fcis-6362	226	47	and	and	CCONJ
fcis-6362	226	48	video	video	NOUN
fcis-6362	226	49	games	game	NOUN
fcis-6362	226	50	.	.	PUNCT
fcis-6362	227	1	the	the	DET
fcis-6362	227	2	imdb	imdb	NOUN
fcis-6362	227	3	[	[	X
fcis-6362	227	4	25	25	NUM
fcis-6362	227	5	]	]	X
fcis-6362	227	6	dataset	dataset	NOUN
fcis-6362	227	7	contains	contain	VERB
fcis-6362	227	8	50,000	50,000	NUM
fcis-6362	227	9	highly	highly	ADV
fcis-6362	227	10	polarized	polarize	VERB
fcis-6362	227	11	reviews	review	NOUN
fcis-6362	227	12	from	from	ADP
fcis-6362	227	13	the	the	DET
fcis-6362	227	14	database	database	NOUN
fcis-6362	227	15	.	.	PUNCT
fcis-6362	228	1	amazon	amazon	PROPN
fcis-6362	229	1	[	[	X
fcis-6362	229	2	26	26	NUM
fcis-6362	229	3	]	]	PUNCT
fcis-6362	229	4	is	be	AUX
fcis-6362	229	5	a	a	DET
fcis-6362	229	6	large	large	ADJ
fcis-6362	229	7	-	-	PUNCT
fcis-6362	229	8	scale	scale	NOUN
fcis-6362	229	9	dataset	dataset	NOUN
fcis-6362	229	10	provided	provide	VERB
fcis-6362	229	11	by	by	ADP
fcis-6362	229	12	amazon	amazon	NOUN
fcis-6362	229	13	,	,	PUNCT
fcis-6362	229	14	which	which	PRON
fcis-6362	229	15	contains	contain	VERB
fcis-6362	229	16	millions	million	NOUN
fcis-6362	229	17	of	of	ADP
fcis-6362	229	18	customer	customer	NOUN
fcis-6362	229	19	reviews	review	NOUN
fcis-6362	229	20	and	and	CCONJ
fcis-6362	229	21	star	star	NOUN
fcis-6362	229	22	ratings	rating	NOUN
fcis-6362	229	23	.	.	PUNCT
fcis-6362	230	1	these	these	DET
fcis-6362	230	2	reviews	review	NOUN
fcis-6362	230	3	cover	cover	VERB
fcis-6362	230	4	various	various	ADJ
fcis-6362	230	5	categories	category	NOUN
fcis-6362	230	6	of	of	ADP
fcis-6362	230	7	products	product	NOUN
fcis-6362	230	8	,	,	PUNCT
fcis-6362	230	9	ranging	range	VERB
fcis-6362	230	10	from	from	ADP
fcis-6362	230	11	books	book	NOUN
fcis-6362	230	12	,	,	PUNCT
fcis-6362	230	13	electronic	electronic	ADJ
fcis-6362	230	14	products	product	NOUN
fcis-6362	230	15	,	,	PUNCT
fcis-6362	230	16	household	household	NOUN
fcis-6362	230	17	items	item	NOUN
fcis-6362	230	18	to	to	ADP
fcis-6362	230	19	food	food	NOUN
fcis-6362	230	20	,	,	PUNCT
fcis-6362	230	21	health	health	NOUN
fcis-6362	230	22	care	care	NOUN
fcis-6362	230	23	,	,	PUNCT
fcis-6362	230	24	clothing	clothing	NOUN
fcis-6362	230	25	and	and	CCONJ
fcis-6362	230	26	more	more	ADJ
fcis-6362	230	27	.	.	PUNCT
fcis-6362	231	1	4.2	4.2	NUM
fcis-6362	231	2	.	.	PUNCT
fcis-6362	232	1	experiment	experiment	NOUN
fcis-6362	232	2	settings	setting	NOUN
fcis-6362	232	3	the	the	DET
fcis-6362	232	4	machine	machine	NOUN
fcis-6362	232	5	used	use	VERB
fcis-6362	232	6	in	in	ADP
fcis-6362	232	7	this	this	DET
fcis-6362	232	8	test	test	NOUN
fcis-6362	232	9	consists	consist	VERB
fcis-6362	232	10	of	of	ADP
fcis-6362	232	11	amd	amd	ADJ
fcis-6362	232	12	ryzen	ryzen	ADJ
fcis-6362	232	13	3600	3600	NUM
fcis-6362	232	14	processor	processor	NOUN
fcis-6362	232	15	,	,	PUNCT
fcis-6362	232	16	nvidia	nvidia	PROPN
fcis-6362	232	17	rtx	rtx	PROPN
fcis-6362	232	18	3090	3090	NUM
fcis-6362	232	19	graphics	graphic	NOUN
fcis-6362	232	20	card	card	NOUN
fcis-6362	232	21	,	,	PUNCT
fcis-6362	232	22	32	32	NUM
fcis-6362	232	23	gb	gb	NOUN
fcis-6362	232	24	memory	memory	NOUN
fcis-6362	232	25	and	and	CCONJ
fcis-6362	232	26	win10	win10	PROPN
fcis-6362	232	27	operating	operating	NOUN
fcis-6362	232	28	system	system	NOUN
fcis-6362	232	29	.	.	PUNCT
fcis-6362	233	1	python	python	PROPN
fcis-6362	233	2	version	version	NOUN
fcis-6362	233	3	is	be	AUX
fcis-6362	233	4	3.8.5	3.8.5	NUM
fcis-6362	233	5	and	and	CCONJ
fcis-6362	233	6	pytorch	pytorch	NOUN
fcis-6362	233	7	version	version	NOUN
fcis-6362	233	8	is	be	AUX
fcis-6362	233	9	1.9.0+cu111	1.9.0+cu111	NUM
fcis-6362	233	10	.	.	PUNCT
fcis-6362	234	1	we	we	PRON
fcis-6362	234	2	use	use	VERB
fcis-6362	234	3	roberta[27	roberta[27	NOUN
fcis-6362	234	4	]	]	PUNCT
fcis-6362	234	5	,	,	PUNCT
fcis-6362	234	6	an	an	DET
fcis-6362	234	7	improved	improved	ADJ
fcis-6362	234	8	model	model	NOUN
fcis-6362	234	9	based	base	VERB
fcis-6362	234	10	on	on	ADP
fcis-6362	234	11	the	the	DET
fcis-6362	234	12	bert	bert	PROPN
fcis-6362	234	13	model	model	NOUN
fcis-6362	234	14	,	,	PUNCT
fcis-6362	234	15	as	as	ADP
fcis-6362	234	16	the	the	DET
fcis-6362	234	17	framework	framework	NOUN
fcis-6362	234	18	of	of	ADP
fcis-6362	234	19	evaluation	evaluation	NOUN
fcis-6362	234	20	sig	sig	NOUN
fcis-6362	234	21	-	-	NOUN
fcis-6362	234	22	loss	loss	NOUN
fcis-6362	234	23	.	.	PUNCT
fcis-6362	235	1	we	we	PRON
fcis-6362	235	2	employ	employ	VERB
fcis-6362	235	3	hugging	hug	VERB
fcis-6362	235	4	face	face	NOUN
fcis-6362	235	5	library	library	NOUN
fcis-6362	235	6	[	[	X
fcis-6362	235	7	28	28	NUM
fcis-6362	235	8	]	]	PUNCT
fcis-6362	235	9	to	to	PART
fcis-6362	235	10	load	load	VERB
fcis-6362	235	11	and	and	CCONJ
fcis-6362	235	12	instantiate	instantiate	VERB
fcis-6362	235	13	the	the	DET
fcis-6362	235	14	pre	pre	ADJ
fcis-6362	235	15	-	-	ADJ
fcis-6362	235	16	trained	train	VERB
fcis-6362	235	17	roberta	roberta	PROPN
fcis-6362	235	18	model	model	NOUN
fcis-6362	235	19	.	.	PUNCT
fcis-6362	236	1	4.3	4.3	NUM
fcis-6362	236	2	.	.	PUNCT
fcis-6362	236	3	baselines	baseline	NOUN
fcis-6362	236	4	in	in	ADP
fcis-6362	236	5	this	this	DET
fcis-6362	236	6	section	section	NOUN
fcis-6362	236	7	,	,	PUNCT
fcis-6362	236	8	we	we	PRON
fcis-6362	236	9	provide	provide	VERB
fcis-6362	236	10	a	a	DET
fcis-6362	236	11	brief	brief	ADJ
fcis-6362	236	12	introduction	introduction	NOUN
fcis-6362	236	13	to	to	ADP
fcis-6362	236	14	the	the	DET
fcis-6362	236	15	compared	compare	VERB
fcis-6362	236	16	baselines	baseline	NOUN
fcis-6362	236	17	.	.	PUNCT
fcis-6362	237	1	fine	fine	ADJ
fcis-6362	237	2	-	-	PUNCT
fcis-6362	237	3	tuning	tuning	NOUN
fcis-6362	237	4	(	(	PUNCT
fcis-6362	237	5	ft	ft	NOUN
fcis-6362	237	6	)	)	PUNCT
fcis-6362	237	7	is	be	AUX
fcis-6362	237	8	a	a	DET
fcis-6362	237	9	typical	typical	ADJ
fcis-6362	237	10	way	way	NOUN
fcis-6362	237	11	of	of	ADP
fcis-6362	237	12	combining	combine	VERB
fcis-6362	237	13	pre	pre	ADJ
fcis-6362	237	14	-	-	ADJ
fcis-6362	237	15	trained	train	VERB
fcis-6362	237	16	models	model	NOUN
fcis-6362	237	17	with	with	ADP
fcis-6362	237	18	downstream	downstream	ADJ
fcis-6362	237	19	tasks	task	NOUN
fcis-6362	237	20	,	,	PUNCT
fcis-6362	237	21	which	which	PRON
fcis-6362	237	22	involves	involve	VERB
fcis-6362	237	23	connecting	connect	VERB
fcis-6362	237	24	the	the	DET
fcis-6362	237	25	[	[	X
fcis-6362	237	26	cls	cls	X
fcis-6362	237	27	]	]	X
fcis-6362	237	28	token	token	NOUN
fcis-6362	237	29	of	of	ADP
fcis-6362	237	30	the	the	DET
fcis-6362	237	31	pre	pre	ADJ
fcis-6362	237	32	-	-	ADJ
fcis-6362	237	33	trained	train	VERB
fcis-6362	237	34	model	model	NOUN
fcis-6362	237	35	to	to	ADP
fcis-6362	237	36	a	a	DET
fcis-6362	237	37	fully	fully	ADV
fcis-6362	237	38	connected	connect	VERB
fcis-6362	237	39	layer	layer	NOUN
fcis-6362	237	40	,	,	PUNCT
fcis-6362	237	41	and	and	CCONJ
fcis-6362	237	42	outputting	output	VERB
fcis-6362	237	43	the	the	DET
fcis-6362	237	44	classification	classification	NOUN
fcis-6362	237	45	results	result	NOUN
fcis-6362	237	46	of	of	ADP
fcis-6362	237	47	the	the	DET
fcis-6362	237	48	model	model	NOUN
fcis-6362	237	49	.	.	PUNCT
fcis-6362	238	1	prompt	prompt	ADJ
fcis-6362	238	2	-	-	PUNCT
fcis-6362	238	3	tuning	tuning	NOUN
fcis-6362	238	4	(	(	PUNCT
fcis-6362	238	5	pt	pt	NOUN
fcis-6362	238	6	)	)	PUNCT
fcis-6362	238	7	is	be	AUX
fcis-6362	238	8	the	the	DET
fcis-6362	238	9	most	most	ADV
fcis-6362	238	10	basic	basic	ADJ
fcis-6362	238	11	way	way	NOUN
fcis-6362	238	12	of	of	ADP
fcis-6362	238	13	prompt	prompt	ADJ
fcis-6362	238	14	learning	learning	NOUN
fcis-6362	238	15	,	,	PUNCT
fcis-6362	238	16	which	which	PRON
fcis-6362	238	17	uses	use	VERB
fcis-6362	238	18	only	only	ADV
fcis-6362	238	19	a	a	DET
fcis-6362	238	20	single	single	ADJ
fcis-6362	238	21	template	template	NOUN
fcis-6362	238	22	and	and	CCONJ
fcis-6362	238	23	a	a	DET
fcis-6362	238	24	single	single	ADJ
fcis-6362	238	25	answer	answer	NOUN
fcis-6362	238	26	space	space	NOUN
fcis-6362	238	27	.	.	PUNCT
fcis-6362	239	1	better	well	ADJ
fcis-6362	239	2	few	few	ADJ
fcis-6362	239	3	-	-	PUNCT
fcis-6362	239	4	shot	shoot	VERB
fcis-6362	239	5	fine	fine	NOUN
fcis-6362	239	6	-	-	PUNCT
fcis-6362	239	7	tuning	tuning	NOUN
fcis-6362	239	8	of	of	ADP
fcis-6362	239	9	language	language	NOUN
fcis-6362	239	10	models(lmbff	models(lmbff	NOUN
fcis-6362	239	11	)	)	PUNCT
fcis-6362	239	12	is	be	AUX
fcis-6362	239	13	the	the	DET
fcis-6362	239	14	method	method	NOUN
fcis-6362	239	15	proposed	propose	VERB
fcis-6362	239	16	by	by	ADP
fcis-6362	239	17	gao	gao	PROPN
fcis-6362	239	18	et	et	PROPN
fcis-6362	239	19	al.includes	al.include	NOUN
fcis-6362	239	20	prompt	prompt	ADJ
fcis-6362	239	21	171	171	NUM
fcis-6362	239	22	based	base	VERB
fcis-6362	239	23	fine	fine	ADV
fcis-6362	239	24	-	-	PUNCT
fcis-6362	239	25	tuning	tuning	NOUN
fcis-6362	239	26	together	together	ADV
fcis-6362	239	27	with	with	ADP
fcis-6362	239	28	a	a	DET
fcis-6362	239	29	novel	novel	ADJ
fcis-6362	239	30	pipeline	pipeline	NOUN
fcis-6362	239	31	for	for	ADP
fcis-6362	239	32	automating	automate	VERB
fcis-6362	239	33	prompt	prompt	ADJ
fcis-6362	239	34	generation	generation	NOUN
fcis-6362	239	35	;	;	PUNCT
fcis-6362	239	36	and	and	CCONJ
fcis-6362	239	37	a	a	DET
fcis-6362	239	38	refined	refined	ADJ
fcis-6362	239	39	strategy	strategy	NOUN
fcis-6362	239	40	for	for	ADP
fcis-6362	239	41	dynamically	dynamically	ADV
fcis-6362	239	42	and	and	CCONJ
fcis-6362	239	43	selectively	selectively	ADV
fcis-6362	239	44	incorporating	incorporate	VERB
fcis-6362	239	45	demonstrations	demonstration	NOUN
fcis-6362	239	46	into	into	ADP
fcis-6362	239	47	each	each	DET
fcis-6362	239	48	context	context	NOUN
fcis-6362	239	49	.	.	PUNCT
fcis-6362	240	1	autoprompt(ap	autoprompt(ap	PROPN
fcis-6362	240	2	)	)	PUNCT
fcis-6362	240	3	is	be	AUX
fcis-6362	240	4	was	be	AUX
fcis-6362	240	5	developed	develop	VERB
fcis-6362	240	6	by	by	ADP
fcis-6362	240	7	shin	shin	PROPN
fcis-6362	240	8	et	et	PROPN
fcis-6362	240	9	al	al	PROPN
fcis-6362	240	10	.	.	PUNCT
fcis-6362	241	1	it	it	PRON
fcis-6362	241	2	selects	select	VERB
fcis-6362	241	3	prompt	prompt	ADJ
fcis-6362	241	4	tokens	token	NOUN
fcis-6362	241	5	from	from	ADP
fcis-6362	241	6	candidate	candidate	NOUN
fcis-6362	241	7	set	set	VERB
fcis-6362	241	8	by	by	ADP
fcis-6362	241	9	gradient	gradient	NOUN
fcis-6362	241	10	.	.	PUNCT
fcis-6362	242	1	bidirectional	bidirectional	ADJ
fcis-6362	242	2	prompt	prompt	ADJ
fcis-6362	242	3	learning	learning	NOUN
fcis-6362	242	4	(	(	PUNCT
fcis-6362	242	5	bpl	bpl	PROPN
fcis-6362	242	6	)	)	PUNCT
fcis-6362	242	7	is	be	AUX
fcis-6362	242	8	our	our	PRON
fcis-6362	242	9	method	method	NOUN
fcis-6362	242	10	.	.	PUNCT
fcis-6362	243	1	it	it	PRON
fcis-6362	243	2	is	be	AUX
fcis-6362	243	3	worth	worth	ADJ
fcis-6362	243	4	mentioning	mention	VERB
fcis-6362	243	5	that	that	SCONJ
fcis-6362	243	6	we	we	PRON
fcis-6362	243	7	have	have	AUX
fcis-6362	243	8	used	use	VERB
fcis-6362	243	9	various	various	ADJ
fcis-6362	243	10	methods	method	NOUN
fcis-6362	243	11	in	in	ADP
fcis-6362	243	12	natural	natural	ADJ
fcis-6362	243	13	language	language	NOUN
fcis-6362	243	14	processing	processing	NOUN
fcis-6362	243	15	to	to	PART
fcis-6362	243	16	expand	expand	VERB
fcis-6362	243	17	the	the	DET
fcis-6362	243	18	training	training	NOUN
fcis-6362	243	19	samples	sample	NOUN
fcis-6362	243	20	,	,	PUNCT
fcis-6362	243	21	including	include	VERB
fcis-6362	243	22	synonym	synonym	NOUN
fcis-6362	243	23	replacement	replacement	NOUN
fcis-6362	243	24	,	,	PUNCT
fcis-6362	243	25	back	back	NOUN
fcis-6362	243	26	-	-	PUNCT
fcis-6362	243	27	translation	translation	NOUN
fcis-6362	243	28	,	,	PUNCT
fcis-6362	243	29	etc	etc	X
fcis-6362	243	30	.	.	X
fcis-6362	244	1	in	in	ADP
fcis-6362	244	2	addition	addition	NOUN
fcis-6362	244	3	,	,	PUNCT
fcis-6362	244	4	we	we	PRON
fcis-6362	244	5	have	have	AUX
fcis-6362	244	6	used	use	VERB
fcis-6362	244	7	part	part	NOUN
fcis-6362	244	8	-	-	PUNCT
fcis-6362	244	9	of	of	ADP
fcis-6362	244	10	-	-	PUNCT
fcis-6362	244	11	speech	speech	NOUN
fcis-6362	244	12	tagging	tagging	NOUN
fcis-6362	244	13	to	to	PART
fcis-6362	244	14	select	select	VERB
fcis-6362	244	15	masked	masked	ADJ
fcis-6362	244	16	tokens	token	NOUN
fcis-6362	244	17	,	,	PUNCT
fcis-6362	244	18	disregarding	disregard	VERB
fcis-6362	244	19	tokens	token	NOUN
fcis-6362	244	20	such	such	ADJ
fcis-6362	244	21	as	as	ADP
fcis-6362	244	22	articles	article	NOUN
fcis-6362	244	23	and	and	CCONJ
fcis-6362	244	24	auxiliary	auxiliary	ADJ
fcis-6362	244	25	verbs	verb	NOUN
fcis-6362	244	26	that	that	PRON
fcis-6362	244	27	do	do	AUX
fcis-6362	244	28	not	not	PART
fcis-6362	244	29	have	have	VERB
fcis-6362	244	30	much	much	ADJ
fcis-6362	244	31	significance	significance	NOUN
fcis-6362	244	32	for	for	ADP
fcis-6362	244	33	bidirectional	bidirectional	ADJ
fcis-6362	244	34	learning	learning	NOUN
fcis-6362	244	35	.	.	PUNCT
fcis-6362	245	1	4.4	4.4	NUM
fcis-6362	245	2	.	.	PUNCT
fcis-6362	246	1	results	result	NOUN
fcis-6362	246	2	table	table	VERB
fcis-6362	246	3	5	5	NUM
fcis-6362	246	4	.	.	PUNCT
fcis-6362	247	1	results	result	NOUN
fcis-6362	247	2	of	of	ADP
fcis-6362	247	3	text	text	NOUN
fcis-6362	247	4	classification	classification	NOUN
fcis-6362	247	5	shot	shot	NOUN
fcis-6362	247	6	method	method	NOUN
fcis-6362	247	7	ag	ag	PROPN
fcis-6362	247	8	yahoo	yahoo	PROPN
fcis-6362	247	9	amazon	amazon	PROPN
fcis-6362	247	10	imdb	imdb	PROPN
fcis-6362	247	11	𝟓	𝟓	PROPN
fcis-6362	247	12	ft	ft	ADP
fcis-6362	247	13	33.4	33.4	NUM
fcis-6362	247	14	23.3	23.3	NUM
fcis-6362	247	15	53.2	53.2	NUM
fcis-6362	247	16	49.4	49.4	NUM
fcis-6362	247	17	pt	pt	NOUN
fcis-6362	247	18	78.5	78.5	NUM
fcis-6362	247	19	60.4	60.4	NUM
fcis-6362	247	20	89.9	89.9	NUM
fcis-6362	247	21	88.7	88.7	NUM
fcis-6362	247	22	lm	lm	PROPN
fcis-6362	247	23	-	-	PUNCT
fcis-6362	247	24	bff	bff	VERB
fcis-6362	247	25	79.8	79.8	NUM
fcis-6362	247	26	63.6	63.6	NUM
fcis-6362	247	27	90.5	90.5	NUM
fcis-6362	247	28	89.3	89.3	NUM
fcis-6362	247	29	ap	ap	PROPN
fcis-6362	247	30	77.2	77.2	NUM
fcis-6362	247	31	64.1	64.1	NUM
fcis-6362	247	32	88.5	88.5	NUM
fcis-6362	247	33	87.2	87.2	NUM
fcis-6362	247	34	bpl	bpl	NOUN
fcis-6362	247	35	80.3	80.3	NUM
fcis-6362	247	36	65.5	65.5	NUM
fcis-6362	247	37	90.3	90.3	NUM
fcis-6362	247	38	89.5	89.5	NUM
fcis-6362	247	39	bpl+	bpl+	PROPN
fcis-6362	247	40	ap	ap	PROPN
fcis-6362	247	41	81.2	81.2	NUM
fcis-6362	247	42	66.3	66.3	NUM
fcis-6362	247	43	90.1	90.1	NUM
fcis-6362	247	44	88.4	88.4	NUM
fcis-6362	247	45	𝟏𝟎	𝟏𝟎	NUM
fcis-6362	247	46	ft	ft	PROPN
fcis-6362	247	47	68.9	68.9	NUM
fcis-6362	247	48	38.7	38.7	NUM
fcis-6362	247	49	78.6	78.6	NUM
fcis-6362	247	50	73.2	73.2	NUM
fcis-6362	247	51	pt	pt	NOUN
fcis-6362	247	52	82.3	82.3	NUM
fcis-6362	247	53	62.1	62.1	NUM
fcis-6362	247	54	90.8	90.8	NUM
fcis-6362	247	55	90.5	90.5	NUM
fcis-6362	247	56	lm	lm	PROPN
fcis-6362	247	57	-	-	PUNCT
fcis-6362	247	58	bff	bff	VERB
fcis-6362	247	59	83.9	83.9	NUM
fcis-6362	247	60	63.6	63.6	NUM
fcis-6362	247	61	91.1	91.1	NUM
fcis-6362	247	62	91.4	91.4	NUM
fcis-6362	247	63	ap	ap	PROPN
fcis-6362	247	64	81.2	81.2	NUM
fcis-6362	247	65	64.6	64.6	NUM
fcis-6362	247	66	90.5	90.5	NUM
fcis-6362	247	67	89.6	89.6	NUM
fcis-6362	247	68	bpl	bpl	NOUN
fcis-6362	247	69	84.4	84.4	NUM
fcis-6362	247	70	64.3	64.3	NUM
fcis-6362	247	71	91.2	91.2	NUM
fcis-6362	247	72	91.2	91.2	NUM
fcis-6362	247	73	bpl+	bpl+	PROPN
fcis-6362	247	74	ap	ap	PROPN
fcis-6362	247	75	85.8	85.8	NUM
fcis-6362	247	76	65.2	65.2	NUM
fcis-6362	247	77	90.5	90.5	NUM
fcis-6362	247	78	92.1	92.1	NUM
fcis-6362	247	79	𝟐𝟎	𝟐𝟎	NUM
fcis-6362	247	80	ft	ft	PART
fcis-6362	247	81	79.8	79.8	NUM
fcis-6362	247	82	53.6	53.6	NUM
fcis-6362	247	83	80.2	80.2	NUM
fcis-6362	247	84	76.8	76.8	NUM
fcis-6362	247	85	pt	pt	NOUN
fcis-6362	247	86	84.5	84.5	NUM
fcis-6362	247	87	66.0	66.0	NUM
fcis-6362	247	88	91.3	91.3	NUM
fcis-6362	247	89	91.8	91.8	NUM
fcis-6362	247	90	lm	lm	PROPN
fcis-6362	247	91	-	-	PUNCT
fcis-6362	247	92	bff	bff	VERB
fcis-6362	248	1	85.6	85.6	NUM
fcis-6362	248	2	67.7	67.7	NUM
fcis-6362	248	3	93.2	93.2	NUM
fcis-6362	248	4	93.3	93.3	NUM
fcis-6362	248	5	ap	ap	PROPN
fcis-6362	248	6	84.8	84.8	NUM
fcis-6362	248	7	66.5	66.5	NUM
fcis-6362	248	8	92.8	92.8	NUM
fcis-6362	248	9	92.9	92.9	NUM
fcis-6362	248	10	bpl	bpl	NOUN
fcis-6362	248	11	85.3	85.3	NUM
fcis-6362	248	12	67.2	67.2	NUM
fcis-6362	248	13	93.3	93.3	NUM
fcis-6362	248	14	92.6	92.6	NUM
fcis-6362	249	1	bpl+	bpl+	PROPN
fcis-6362	250	1	ap	ap	PROPN
fcis-6362	251	1	86.1	86.1	NUM
fcis-6362	251	2	67.3	67.3	NUM
fcis-6362	251	3	93.1	93.1	NUM
fcis-6362	251	4	93.0	93.0	NUM
fcis-6362	251	5	in	in	ADP
fcis-6362	251	6	table	table	NOUN
fcis-6362	251	7	5	5	NUM
fcis-6362	251	8	,	,	PUNCT
fcis-6362	251	9	we	we	PRON
fcis-6362	251	10	compared	compare	VERB
fcis-6362	251	11	the	the	DET
fcis-6362	251	12	performance	performance	NOUN
fcis-6362	251	13	of	of	ADP
fcis-6362	251	14	various	various	ADJ
fcis-6362	251	15	models	model	NOUN
fcis-6362	251	16	with	with	ADP
fcis-6362	251	17	sample	sample	NOUN
fcis-6362	251	18	sizes	size	NOUN
fcis-6362	251	19	of	of	ADP
fcis-6362	251	20	5	5	NUM
fcis-6362	251	21	,	,	PUNCT
fcis-6362	251	22	10	10	NUM
fcis-6362	251	23	,	,	PUNCT
fcis-6362	251	24	and	and	CCONJ
fcis-6362	251	25	20	20	NUM
fcis-6362	251	26	,	,	PUNCT
fcis-6362	251	27	respectively	respectively	ADV
fcis-6362	251	28	.	.	PUNCT
fcis-6362	252	1	the	the	DET
fcis-6362	252	2	results	result	NOUN
fcis-6362	252	3	show	show	VERB
fcis-6362	252	4	that	that	SCONJ
fcis-6362	252	5	compared	compare	VERB
fcis-6362	252	6	to	to	ADP
fcis-6362	252	7	the	the	DET
fcis-6362	252	8	two	two	NUM
fcis-6362	252	9	baseline	baseline	NOUN
fcis-6362	252	10	models	model	NOUN
fcis-6362	252	11	,	,	PUNCT
fcis-6362	252	12	ft	ft	PROPN
fcis-6362	252	13	and	and	CCONJ
fcis-6362	252	14	pt	pt	PROPN
fcis-6362	252	15	,	,	PUNCT
fcis-6362	252	16	our	our	PRON
fcis-6362	252	17	method	method	NOUN
fcis-6362	252	18	can	can	AUX
fcis-6362	252	19	effectively	effectively	ADV
fcis-6362	252	20	improve	improve	VERB
fcis-6362	252	21	the	the	DET
fcis-6362	252	22	model	model	NOUN
fcis-6362	252	23	's	's	PART
fcis-6362	252	24	ability	ability	NOUN
fcis-6362	252	25	in	in	ADP
fcis-6362	252	26	few	few	ADJ
fcis-6362	252	27	-	-	PUNCT
fcis-6362	252	28	shot	shot	NOUN
fcis-6362	252	29	tasks	task	NOUN
fcis-6362	252	30	and	and	CCONJ
fcis-6362	252	31	enable	enable	VERB
fcis-6362	252	32	it	it	PRON
fcis-6362	252	33	to	to	ADP
fcis-6362	252	34	quickly	quickly	ADV
fcis-6362	252	35	boot	boot	VERB
fcis-6362	252	36	.	.	PUNCT
fcis-6362	253	1	our	our	PRON
fcis-6362	253	2	model	model	NOUN
fcis-6362	253	3	can	can	AUX
fcis-6362	253	4	also	also	ADV
fcis-6362	253	5	be	be	AUX
fcis-6362	253	6	combined	combine	VERB
fcis-6362	253	7	with	with	ADP
fcis-6362	253	8	existing	exist	VERB
fcis-6362	253	9	methods	method	NOUN
fcis-6362	253	10	,	,	PUNCT
fcis-6362	253	11	such	such	ADJ
fcis-6362	253	12	as	as	ADP
fcis-6362	253	13	the	the	DET
fcis-6362	253	14	bpl+ap	bpl+ap	ADJ
fcis-6362	253	15	model	model	NOUN
fcis-6362	253	16	in	in	ADP
fcis-6362	253	17	the	the	DET
fcis-6362	253	18	table	table	NOUN
fcis-6362	253	19	,	,	PUNCT
fcis-6362	253	20	which	which	PRON
fcis-6362	253	21	uses	use	VERB
fcis-6362	253	22	both	both	PRON
fcis-6362	253	23	bidirectional	bidirectional	ADJ
fcis-6362	253	24	prompt	prompt	ADJ
fcis-6362	253	25	learning	learning	NOUN
fcis-6362	253	26	and	and	CCONJ
fcis-6362	253	27	auto	auto	NOUN
fcis-6362	253	28	prompt	prompt	ADJ
fcis-6362	253	29	strategies	strategy	NOUN
fcis-6362	253	30	.	.	PUNCT
fcis-6362	254	1	it	it	PRON
fcis-6362	254	2	is	be	AUX
fcis-6362	254	3	worth	worth	ADJ
fcis-6362	254	4	mentioning	mention	VERB
fcis-6362	254	5	that	that	SCONJ
fcis-6362	254	6	compared	compare	VERB
fcis-6362	254	7	to	to	ADP
fcis-6362	254	8	the	the	DET
fcis-6362	254	9	baseline	baseline	NOUN
fcis-6362	254	10	models	model	NOUN
fcis-6362	254	11	,	,	PUNCT
fcis-6362	254	12	the	the	DET
fcis-6362	254	13	variance	variance	NOUN
fcis-6362	254	14	of	of	ADP
fcis-6362	254	15	the	the	DET
fcis-6362	254	16	results	result	NOUN
fcis-6362	254	17	of	of	ADP
fcis-6362	254	18	several	several	ADJ
fcis-6362	254	19	expansion	expansion	NOUN
fcis-6362	254	20	models	model	NOUN
fcis-6362	254	21	has	have	AUX
fcis-6362	254	22	been	be	AUX
fcis-6362	254	23	effectively	effectively	ADV
fcis-6362	254	24	reduced	reduce	VERB
fcis-6362	254	25	,	,	PUNCT
fcis-6362	254	26	demonstrating	demonstrate	VERB
fcis-6362	254	27	that	that	SCONJ
fcis-6362	254	28	these	these	DET
fcis-6362	254	29	models	model	NOUN
fcis-6362	254	30	can	can	AUX
fcis-6362	254	31	more	more	ADV
fcis-6362	254	32	effectively	effectively	ADV
fcis-6362	254	33	extract	extract	VERB
fcis-6362	254	34	the	the	DET
fcis-6362	254	35	language	language	NOUN
fcis-6362	254	36	abilities	ability	NOUN
fcis-6362	254	37	of	of	ADP
fcis-6362	254	38	large	large	ADJ
fcis-6362	254	39	models	model	NOUN
fcis-6362	254	40	.	.	PUNCT
fcis-6362	255	1	5	5	X
fcis-6362	255	2	.	.	X
fcis-6362	255	3	conclusion	conclusion	NOUN
fcis-6362	255	4	prompt	prompt	ADJ
fcis-6362	255	5	learning	learning	NOUN
fcis-6362	255	6	is	be	AUX
fcis-6362	255	7	a	a	DET
fcis-6362	255	8	new	new	ADJ
fcis-6362	255	9	paradigm	paradigm	NOUN
fcis-6362	255	10	in	in	ADP
fcis-6362	255	11	natural	natural	ADJ
fcis-6362	255	12	language	language	NOUN
fcis-6362	255	13	processing	processing	NOUN
fcis-6362	255	14	that	that	PRON
fcis-6362	255	15	has	have	AUX
fcis-6362	255	16	emerged	emerge	VERB
fcis-6362	255	17	in	in	ADP
fcis-6362	255	18	recent	recent	ADJ
fcis-6362	255	19	years	year	NOUN
fcis-6362	255	20	.	.	PUNCT
fcis-6362	256	1	it	it	PRON
fcis-6362	256	2	can	can	AUX
fcis-6362	256	3	effectively	effectively	ADV
fcis-6362	256	4	utilize	utilize	VERB
fcis-6362	256	5	the	the	DET
fcis-6362	256	6	language	language	NOUN
fcis-6362	256	7	abilities	ability	NOUN
fcis-6362	256	8	learned	learn	VERB
fcis-6362	256	9	by	by	ADP
fcis-6362	256	10	large	large	ADJ
fcis-6362	256	11	-	-	PUNCT
fcis-6362	256	12	scale	scale	NOUN
fcis-6362	256	13	models	model	NOUN
fcis-6362	256	14	and	and	CCONJ
fcis-6362	256	15	unify	unify	VERB
fcis-6362	256	16	the	the	DET
fcis-6362	256	17	training	training	NOUN
fcis-6362	256	18	methods	method	NOUN
fcis-6362	256	19	for	for	ADP
fcis-6362	256	20	downstream	downstream	ADJ
fcis-6362	256	21	tasks	task	NOUN
fcis-6362	256	22	.	.	PUNCT
fcis-6362	257	1	in	in	ADP
fcis-6362	257	2	practical	practical	ADJ
fcis-6362	257	3	scenarios	scenario	NOUN
fcis-6362	257	4	,	,	PUNCT
fcis-6362	257	5	the	the	DET
fcis-6362	257	6	sample	sample	NOUN
fcis-6362	257	7	set	set	VERB
fcis-6362	257	8	size	size	NOUN
fcis-6362	257	9	is	be	AUX
fcis-6362	257	10	often	often	ADV
fcis-6362	257	11	insufficient	insufficient	ADJ
fcis-6362	257	12	or	or	CCONJ
fcis-6362	257	13	unannotated	unannotate	VERB
fcis-6362	257	14	,	,	PUNCT
fcis-6362	257	15	and	and	CCONJ
fcis-6362	257	16	research	research	NOUN
fcis-6362	257	17	on	on	ADP
fcis-6362	257	18	few	few	ADJ
fcis-6362	257	19	-	-	PUNCT
fcis-6362	257	20	shot	shot	NOUN
fcis-6362	257	21	learning	learning	NOUN
fcis-6362	257	22	requires	require	VERB
fcis-6362	257	23	models	model	NOUN
fcis-6362	257	24	to	to	PART
fcis-6362	257	25	quickly	quickly	ADV
fcis-6362	257	26	obtain	obtain	VERB
fcis-6362	257	27	good	good	ADJ
fcis-6362	257	28	performance	performance	NOUN
fcis-6362	257	29	on	on	ADP
fcis-6362	257	30	small	small	ADJ
fcis-6362	257	31	training	training	NOUN
fcis-6362	257	32	and	and	CCONJ
fcis-6362	257	33	validation	validation	NOUN
fcis-6362	257	34	sets	set	NOUN
fcis-6362	257	35	.	.	PUNCT
fcis-6362	258	1	prompt	prompt	ADJ
fcis-6362	258	2	learning	learning	NOUN
fcis-6362	258	3	has	have	AUX
fcis-6362	258	4	shown	show	VERB
fcis-6362	258	5	strong	strong	ADJ
fcis-6362	258	6	competitiveness	competitiveness	NOUN
fcis-6362	258	7	in	in	ADP
fcis-6362	258	8	the	the	DET
fcis-6362	258	9	field	field	NOUN
fcis-6362	258	10	of	of	ADP
fcis-6362	258	11	few	few	ADJ
fcis-6362	258	12	-	-	PUNCT
fcis-6362	258	13	shot	shot	NOUN
fcis-6362	258	14	learning	learning	NOUN
fcis-6362	258	15	,	,	PUNCT
fcis-6362	258	16	and	and	CCONJ
fcis-6362	258	17	this	this	DET
fcis-6362	258	18	article	article	NOUN
fcis-6362	258	19	proposes	propose	VERB
fcis-6362	258	20	bidirectional	bidirectional	ADJ
fcis-6362	258	21	prompt	prompt	ADJ
fcis-6362	258	22	learning	learning	NOUN
fcis-6362	258	23	based	base	VERB
fcis-6362	258	24	on	on	ADP
fcis-6362	258	25	the	the	DET
fcis-6362	258	26	prompt	prompt	ADJ
fcis-6362	258	27	learning	learning	NOUN
fcis-6362	258	28	paradigm	paradigm	NOUN
fcis-6362	258	29	.	.	PUNCT
fcis-6362	259	1	by	by	ADP
fcis-6362	259	2	introducing	introduce	VERB
fcis-6362	259	3	a	a	DET
fcis-6362	259	4	conjugate	conjugate	ADJ
fcis-6362	259	5	task	task	NOUN
fcis-6362	259	6	,	,	PUNCT
fcis-6362	259	7	the	the	DET
fcis-6362	259	8	model	model	NOUN
fcis-6362	259	9	's	's	PART
fcis-6362	259	10	ability	ability	NOUN
fcis-6362	259	11	to	to	PART
fcis-6362	259	12	perform	perform	VERB
fcis-6362	259	13	few	few	ADJ
fcis-6362	259	14	-	-	PUNCT
fcis-6362	259	15	shot	shot	NOUN
fcis-6362	259	16	tasks	task	NOUN
fcis-6362	259	17	can	can	AUX
fcis-6362	259	18	be	be	AUX
fcis-6362	259	19	further	far	ADV
fcis-6362	259	20	improved	improve	VERB
fcis-6362	259	21	.	.	PUNCT
fcis-6362	260	1	it	it	PRON
fcis-6362	260	2	can	can	AUX
fcis-6362	260	3	also	also	ADV
fcis-6362	260	4	be	be	AUX
fcis-6362	260	5	easily	easily	ADV
fcis-6362	260	6	integrated	integrate	VERB
fcis-6362	260	7	with	with	ADP
fcis-6362	260	8	most	most	ADJ
fcis-6362	260	9	work	work	NOUN
fcis-6362	260	10	.	.	PUNCT
fcis-6362	261	1	references	reference	NOUN
fcis-6362	261	2	[	[	X
fcis-6362	261	3	1	1	NUM
fcis-6362	261	4	]	]	X
fcis-6362	261	5	chomsky	chomsky	PROPN
fcis-6362	261	6	,	,	PUNCT
fcis-6362	261	7	n.	n.	PROPN
fcis-6362	261	8	(	(	PUNCT
fcis-6362	261	9	2002	2002	NUM
fcis-6362	261	10	)	)	PUNCT
fcis-6362	261	11	.	.	PUNCT
fcis-6362	262	1	syntactic	syntactic	ADJ
fcis-6362	262	2	structures	structure	NOUN
fcis-6362	262	3	.	.	PUNCT
fcis-6362	263	1	mouton	mouton	PROPN
fcis-6362	263	2	de	de	PROPN
fcis-6362	263	3	gruyter	gruyter	NOUN
fcis-6362	263	4	.	.	PUNCT
fcis-6362	264	1	[	[	X
fcis-6362	264	2	2	2	NUM
fcis-6362	264	3	]	]	X
fcis-6362	264	4	platt	platt	NOUN
fcis-6362	264	5	,	,	PUNCT
fcis-6362	264	6	j.	j.	PROPN
fcis-6362	264	7	(	(	PUNCT
fcis-6362	264	8	1998	1998	NUM
fcis-6362	264	9	)	)	PUNCT
fcis-6362	264	10	.	.	PUNCT
fcis-6362	265	1	making	make	VERB
fcis-6362	265	2	large	large	ADJ
fcis-6362	265	3	-	-	PUNCT
fcis-6362	265	4	scale	scale	NOUN
fcis-6362	265	5	support	support	NOUN
fcis-6362	265	6	vector	vector	NOUN
fcis-6362	265	7	machine	machine	NOUN
fcis-6362	265	8	learning	learn	VERB
fcis-6362	265	9	practical	practical	ADJ
fcis-6362	265	10	.	.	PUNCT
fcis-6362	266	1	advances	advance	NOUN
fcis-6362	266	2	in	in	ADP
fcis-6362	266	3	kernel	kernel	PROPN
fcis-6362	266	4	methods	method	NOUN
fcis-6362	266	5	:	:	PUNCT
fcis-6362	266	6	support	support	VERB
fcis-6362	266	7	vector	vector	NOUN
fcis-6362	266	8	machines	machine	NOUN
fcis-6362	266	9	.	.	PUNCT
fcis-6362	267	1	[	[	X
fcis-6362	267	2	3	3	X
fcis-6362	267	3	]	]	X
fcis-6362	267	4	eddy	eddy	PROPN
fcis-6362	267	5	,	,	PUNCT
fcis-6362	267	6	s.	s.	PROPN
fcis-6362	267	7	r.	r.	PROPN
fcis-6362	267	8	(	(	PUNCT
fcis-6362	267	9	1996	1996	NUM
fcis-6362	267	10	)	)	PUNCT
fcis-6362	267	11	.	.	PUNCT
fcis-6362	268	1	hidden	hide	VERB
fcis-6362	268	2	markov	markov	NOUN
fcis-6362	268	3	models	model	NOUN
fcis-6362	268	4	.	.	PUNCT
fcis-6362	269	1	current	current	ADJ
fcis-6362	269	2	opinion	opinion	NOUN
fcis-6362	269	3	in	in	ADP
fcis-6362	269	4	structural	structural	ADJ
fcis-6362	269	5	biology	biology	NOUN
fcis-6362	269	6	,	,	PUNCT
fcis-6362	269	7	6(3	6(3	NUM
fcis-6362	269	8	)	)	PUNCT
fcis-6362	269	9	,	,	PUNCT
fcis-6362	269	10	361	361	NUM
fcis-6362	269	11	-	-	SYM
fcis-6362	269	12	365	365	NUM
fcis-6362	269	13	.	.	PUNCT
fcis-6362	270	1	[	[	X
fcis-6362	270	2	4	4	NUM
fcis-6362	270	3	]	]	X
fcis-6362	270	4	el	el	PROPN
fcis-6362	270	5	-	-	PUNCT
fcis-6362	270	6	din	din	PROPN
fcis-6362	270	7	,	,	PUNCT
fcis-6362	270	8	d.	d.	PROPN
fcis-6362	270	9	m.	m.	PROPN
fcis-6362	270	10	(	(	PUNCT
fcis-6362	270	11	2016	2016	NUM
fcis-6362	270	12	)	)	PUNCT
fcis-6362	270	13	.	.	PUNCT
fcis-6362	271	1	enhancement	enhancement	NOUN
fcis-6362	271	2	bag	bag	NOUN
fcis-6362	271	3	-	-	PUNCT
fcis-6362	271	4	of	of	ADP
fcis-6362	271	5	-	-	PUNCT
fcis-6362	271	6	words	word	NOUN
fcis-6362	271	7	model	model	NOUN
fcis-6362	271	8	for	for	ADP
fcis-6362	271	9	solving	solve	VERB
fcis-6362	271	10	the	the	DET
fcis-6362	271	11	challenges	challenge	NOUN
fcis-6362	271	12	of	of	ADP
fcis-6362	271	13	sentiment	sentiment	NOUN
fcis-6362	271	14	analysis	analysis	NOUN
fcis-6362	271	15	.	.	PUNCT
fcis-6362	272	1	international	international	ADJ
fcis-6362	272	2	journal	journal	NOUN
fcis-6362	272	3	of	of	ADP
fcis-6362	272	4	advanced	advanced	ADJ
fcis-6362	272	5	computer	computer	NOUN
fcis-6362	272	6	science	science	NOUN
fcis-6362	272	7	and	and	CCONJ
fcis-6362	272	8	applications	application	NOUN
fcis-6362	272	9	,	,	PUNCT
fcis-6362	272	10	7(1	7(1	NUM
fcis-6362	272	11	)	)	PUNCT
fcis-6362	272	12	.	.	PUNCT
fcis-6362	273	1	[	[	X
fcis-6362	273	2	5	5	NUM
fcis-6362	273	3	]	]	X
fcis-6362	273	4	bengio	bengio	NOUN
fcis-6362	273	5	,	,	PUNCT
fcis-6362	273	6	y.	y.	PROPN
fcis-6362	273	7	,	,	PUNCT
fcis-6362	273	8	ducharme	ducharme	PROPN
fcis-6362	273	9	,	,	PUNCT
fcis-6362	273	10	r.	r.	PROPN
fcis-6362	273	11	,	,	PUNCT
fcis-6362	273	12	&	&	CCONJ
fcis-6362	273	13	vincent	vincent	PROPN
fcis-6362	273	14	,	,	PUNCT
fcis-6362	273	15	p.	p.	NOUN
fcis-6362	273	16	(	(	PUNCT
fcis-6362	273	17	2000	2000	NUM
fcis-6362	273	18	)	)	PUNCT
fcis-6362	273	19	.	.	PUNCT
fcis-6362	274	1	a	a	DET
fcis-6362	274	2	neural	neural	ADJ
fcis-6362	274	3	probabilistic	probabilistic	ADJ
fcis-6362	274	4	language	language	NOUN
fcis-6362	274	5	model	model	NOUN
fcis-6362	274	6	.	.	PUNCT
fcis-6362	275	1	advances	advance	NOUN
fcis-6362	275	2	in	in	ADP
fcis-6362	275	3	neural	neural	ADJ
fcis-6362	275	4	information	information	NOUN
fcis-6362	275	5	processing	processing	NOUN
fcis-6362	275	6	systems	system	NOUN
fcis-6362	275	7	,	,	PUNCT
fcis-6362	275	8	13	13	NUM
fcis-6362	275	9	.	.	PUNCT
fcis-6362	276	1	[	[	X
fcis-6362	276	2	6	6	NUM
fcis-6362	276	3	]	]	SYM
fcis-6362	276	4	kenton	kenton	PROPN
fcis-6362	276	5	,	,	PUNCT
fcis-6362	276	6	j.	j.	PROPN
fcis-6362	276	7	d.	d.	PROPN
fcis-6362	276	8	m.	m.	PROPN
fcis-6362	276	9	w.	w.	PROPN
fcis-6362	276	10	c.	c.	PROPN
fcis-6362	276	11	,	,	PUNCT
fcis-6362	276	12	&	&	CCONJ
fcis-6362	276	13	toutanova	toutanova	PROPN
fcis-6362	276	14	,	,	PUNCT
fcis-6362	276	15	l.	l.	PROPN
fcis-6362	276	16	k.	k.	PROPN
fcis-6362	276	17	(	(	PUNCT
fcis-6362	276	18	2019	2019	NUM
fcis-6362	276	19	)	)	PUNCT
fcis-6362	276	20	.	.	PUNCT
fcis-6362	277	1	bert	bert	PROPN
fcis-6362	277	2	:	:	PUNCT
fcis-6362	277	3	pre	pre	ADJ
fcis-6362	277	4	-	-	NOUN
fcis-6362	277	5	training	training	NOUN
fcis-6362	277	6	of	of	ADP
fcis-6362	277	7	deep	deep	ADJ
fcis-6362	277	8	bidirectional	bidirectional	ADJ
fcis-6362	277	9	transformers	transformer	NOUN
fcis-6362	277	10	for	for	ADP
fcis-6362	277	11	language	language	NOUN
fcis-6362	277	12	understanding	understanding	NOUN
fcis-6362	277	13	.	.	PUNCT
fcis-6362	278	1	in	in	ADP
fcis-6362	278	2	proceedings	proceeding	NOUN
fcis-6362	278	3	of	of	ADP
fcis-6362	278	4	naacl	naacl	PROPN
fcis-6362	278	5	-	-	PUNCT
fcis-6362	278	6	hlt	hlt	PROPN
fcis-6362	278	7	(	(	PUNCT
fcis-6362	278	8	pp	pp	ADJ
fcis-6362	278	9	.	.	PUNCT
fcis-6362	278	10	41714186	41714186	NUM
fcis-6362	278	11	)	)	PUNCT
fcis-6362	278	12	.	.	PUNCT
fcis-6362	279	1	[	[	X
fcis-6362	279	2	7	7	NUM
fcis-6362	279	3	]	]	X
fcis-6362	279	4	brown	brown	ADJ
fcis-6362	279	5	,	,	PUNCT
fcis-6362	279	6	t.	t.	PROPN
fcis-6362	279	7	,	,	PUNCT
fcis-6362	279	8	mann	mann	PROPN
fcis-6362	279	9	,	,	PUNCT
fcis-6362	279	10	b.	b.	PROPN
fcis-6362	279	11	,	,	PUNCT
fcis-6362	279	12	ryder	ryder	PROPN
fcis-6362	279	13	,	,	PUNCT
fcis-6362	279	14	n.	n.	NOUN
fcis-6362	279	15	,	,	PUNCT
fcis-6362	279	16	subbiah	subbiah	PROPN
fcis-6362	279	17	,	,	PUNCT
fcis-6362	279	18	m.	m.	NOUN
fcis-6362	279	19	,	,	PUNCT
fcis-6362	279	20	kaplan	kaplan	PROPN
fcis-6362	279	21	,	,	PUNCT
fcis-6362	279	22	j.	j.	PROPN
fcis-6362	279	23	d.	d.	PROPN
fcis-6362	279	24	,	,	PUNCT
fcis-6362	279	25	dhariwal	dhariwal	NOUN
fcis-6362	279	26	,	,	PUNCT
fcis-6362	279	27	p.	p.	PROPN
fcis-6362	279	28	,	,	PUNCT
fcis-6362	279	29	...	...	PUNCT
fcis-6362	279	30	&	&	CCONJ
fcis-6362	279	31	amodei	amodei	PROPN
fcis-6362	279	32	,	,	PUNCT
fcis-6362	279	33	d.	d.	PROPN
fcis-6362	279	34	(	(	PUNCT
fcis-6362	279	35	2020	2020	NUM
fcis-6362	279	36	)	)	PUNCT
fcis-6362	279	37	.	.	PUNCT
fcis-6362	280	1	language	language	NOUN
fcis-6362	280	2	models	model	NOUN
fcis-6362	280	3	are	be	AUX
fcis-6362	280	4	few	few	ADJ
fcis-6362	280	5	-	-	PUNCT
fcis-6362	280	6	shot	shot	NOUN
fcis-6362	280	7	learners	learner	NOUN
fcis-6362	280	8	.	.	PUNCT
fcis-6362	281	1	advances	advance	NOUN
fcis-6362	281	2	in	in	ADP
fcis-6362	281	3	neural	neural	ADJ
fcis-6362	281	4	information	information	NOUN
fcis-6362	281	5	processing	processing	NOUN
fcis-6362	281	6	systems	system	NOUN
fcis-6362	281	7	,	,	PUNCT
fcis-6362	281	8	33	33	NUM
fcis-6362	281	9	,	,	PUNCT
fcis-6362	281	10	1877	1877	NUM
fcis-6362	281	11	-	-	SYM
fcis-6362	281	12	1901	1901	NUM
fcis-6362	281	13	.	.	PUNCT
fcis-6362	282	1	[	[	X
fcis-6362	282	2	8	8	NUM
fcis-6362	282	3	]	]	X
fcis-6362	282	4	lewis	lewis	PROPN
fcis-6362	282	5	,	,	PUNCT
fcis-6362	282	6	p.	p.	PROPN
fcis-6362	282	7	,	,	PUNCT
fcis-6362	282	8	perez	perez	PROPN
fcis-6362	282	9	,	,	PUNCT
fcis-6362	282	10	e.	e.	PROPN
fcis-6362	282	11	,	,	PUNCT
fcis-6362	282	12	piktus	piktus	PROPN
fcis-6362	282	13	,	,	PUNCT
fcis-6362	282	14	a.	a.	NOUN
fcis-6362	282	15	,	,	PUNCT
fcis-6362	282	16	petroni	petroni	NOUN
fcis-6362	282	17	,	,	PUNCT
fcis-6362	282	18	f.	f.	PROPN
fcis-6362	282	19	,	,	PUNCT
fcis-6362	282	20	karpukhin	karpukhin	PROPN
fcis-6362	282	21	,	,	PUNCT
fcis-6362	282	22	v.	v.	PROPN
fcis-6362	282	23	,	,	PUNCT
fcis-6362	282	24	goyal	goyal	PROPN
fcis-6362	282	25	,	,	PUNCT
fcis-6362	282	26	n.	n.	NOUN
fcis-6362	282	27	,	,	PUNCT
fcis-6362	282	28	...	...	PUNCT
fcis-6362	282	29	&	&	CCONJ
fcis-6362	282	30	kiela	kiela	PROPN
fcis-6362	282	31	,	,	PUNCT
fcis-6362	282	32	d.	d.	PROPN
fcis-6362	282	33	(	(	PUNCT
fcis-6362	282	34	2020	2020	NUM
fcis-6362	282	35	)	)	PUNCT
fcis-6362	282	36	.	.	PUNCT
fcis-6362	283	1	retrieval	retrieval	NOUN
fcis-6362	283	2	-	-	PUNCT
fcis-6362	283	3	augmented	augment	VERB
fcis-6362	283	4	generation	generation	NOUN
fcis-6362	283	5	for	for	ADP
fcis-6362	283	6	knowledge	knowledge	NOUN
fcis-6362	283	7	-	-	PUNCT
fcis-6362	283	8	intensive	intensive	ADJ
fcis-6362	283	9	nlp	nlp	NOUN
fcis-6362	283	10	tasks	task	NOUN
fcis-6362	283	11	.	.	PUNCT
fcis-6362	284	1	advances	advance	NOUN
fcis-6362	284	2	in	in	ADP
fcis-6362	284	3	neural	neural	ADJ
fcis-6362	284	4	information	information	NOUN
fcis-6362	284	5	processing	processing	NOUN
fcis-6362	284	6	systems	system	NOUN
fcis-6362	284	7	,	,	PUNCT
fcis-6362	284	8	33	33	NUM
fcis-6362	284	9	,	,	PUNCT
fcis-6362	284	10	9459	9459	NUM
fcis-6362	284	11	-	-	SYM
fcis-6362	284	12	9474	9474	NUM
fcis-6362	284	13	.	.	PUNCT
fcis-6362	285	1	[	[	X
fcis-6362	285	2	9	9	NUM
fcis-6362	285	3	]	]	X
fcis-6362	285	4	jiang	jiang	PROPN
fcis-6362	285	5	,	,	PUNCT
fcis-6362	285	6	z.	z.	PROPN
fcis-6362	285	7	,	,	PUNCT
fcis-6362	285	8	xu	xu	PROPN
fcis-6362	285	9	,	,	PUNCT
fcis-6362	285	10	f.	f.	PROPN
fcis-6362	285	11	f.	f.	PROPN
fcis-6362	285	12	,	,	PUNCT
fcis-6362	285	13	araki	araki	PROPN
fcis-6362	285	14	,	,	PUNCT
fcis-6362	285	15	j.	j.	PROPN
fcis-6362	285	16	,	,	PUNCT
fcis-6362	285	17	&	&	CCONJ
fcis-6362	285	18	neubig	neubig	PROPN
fcis-6362	285	19	,	,	PUNCT
fcis-6362	285	20	g.	g.	PROPN
fcis-6362	285	21	(	(	PUNCT
fcis-6362	285	22	2020	2020	NUM
fcis-6362	285	23	)	)	PUNCT
fcis-6362	285	24	.	.	PUNCT
fcis-6362	286	1	how	how	SCONJ
fcis-6362	286	2	can	can	AUX
fcis-6362	286	3	we	we	PRON
fcis-6362	286	4	know	know	VERB
fcis-6362	286	5	what	what	PRON
fcis-6362	286	6	language	language	NOUN
fcis-6362	286	7	models	model	NOUN
fcis-6362	286	8	know	know	VERB
fcis-6362	286	9	?	?	PUNCT
fcis-6362	286	10	.	.	PUNCT
fcis-6362	287	1	transactions	transaction	NOUN
fcis-6362	287	2	of	of	ADP
fcis-6362	287	3	the	the	DET
fcis-6362	287	4	association	association	NOUN
fcis-6362	287	5	for	for	ADP
fcis-6362	287	6	computational	computational	ADJ
fcis-6362	287	7	linguistics	linguistic	NOUN
fcis-6362	287	8	,	,	PUNCT
fcis-6362	287	9	8	8	NUM
fcis-6362	287	10	,	,	PUNCT
fcis-6362	287	11	423	423	NUM
fcis-6362	287	12	-	-	SYM
fcis-6362	287	13	438	438	NUM
fcis-6362	287	14	.	.	PUNCT
fcis-6362	288	1	[	[	X
fcis-6362	288	2	10	10	NUM
fcis-6362	288	3	]	]	X
fcis-6362	288	4	radford	radford	PROPN
fcis-6362	288	5	,	,	PUNCT
fcis-6362	288	6	a.	a.	PROPN
fcis-6362	288	7	,	,	PUNCT
fcis-6362	288	8	narasimhan	narasimhan	PROPN
fcis-6362	288	9	,	,	PUNCT
fcis-6362	288	10	k.	k.	PROPN
fcis-6362	288	11	,	,	PUNCT
fcis-6362	288	12	salimans	saliman	NOUN
fcis-6362	288	13	,	,	PUNCT
fcis-6362	288	14	t.	t.	PROPN
fcis-6362	288	15	,	,	PUNCT
fcis-6362	288	16	&	&	CCONJ
fcis-6362	288	17	sutskever	sutskever	PROPN
fcis-6362	288	18	,	,	PUNCT
fcis-6362	288	19	i.	i.	PROPN
fcis-6362	288	20	(	(	PUNCT
fcis-6362	288	21	2018	2018	NUM
fcis-6362	288	22	)	)	PUNCT
fcis-6362	288	23	.	.	PUNCT
fcis-6362	289	1	improving	improve	VERB
fcis-6362	289	2	language	language	NOUN
fcis-6362	289	3	understanding	understanding	NOUN
fcis-6362	289	4	by	by	ADP
fcis-6362	289	5	generative	generative	ADJ
fcis-6362	289	6	pretraining	pretraine	VERB
fcis-6362	289	7	..	..	PUNCT
fcis-6362	290	1	[	[	X
fcis-6362	290	2	11	11	NUM
fcis-6362	290	3	]	]	SYM
fcis-6362	290	4	li	li	PROPN
fcis-6362	290	5	,	,	PUNCT
fcis-6362	290	6	x.	x.	PROPN
fcis-6362	290	7	l.	l.	PROPN
fcis-6362	290	8	,	,	PUNCT
fcis-6362	290	9	&	&	CCONJ
fcis-6362	290	10	liang	liang	PROPN
fcis-6362	290	11	,	,	PUNCT
fcis-6362	290	12	p.	p.	NOUN
fcis-6362	290	13	(	(	PUNCT
fcis-6362	290	14	2021	2021	NUM
fcis-6362	290	15	,	,	PUNCT
fcis-6362	290	16	august	august	PROPN
fcis-6362	290	17	)	)	PUNCT
fcis-6362	290	18	.	.	PUNCT
fcis-6362	291	1	prefix	prefix	NOUN
fcis-6362	291	2	-	-	PUNCT
fcis-6362	291	3	tuning	tuning	NOUN
fcis-6362	291	4	:	:	PUNCT
fcis-6362	291	5	optimizing	optimize	VERB
fcis-6362	291	6	continuous	continuous	ADJ
fcis-6362	291	7	prompts	prompt	NOUN
fcis-6362	291	8	for	for	ADP
fcis-6362	291	9	generation	generation	NOUN
fcis-6362	291	10	.	.	PUNCT
fcis-6362	292	1	in	in	ADP
fcis-6362	292	2	proceedings	proceeding	NOUN
fcis-6362	292	3	of	of	ADP
fcis-6362	292	4	the	the	DET
fcis-6362	292	5	59th	59th	ADJ
fcis-6362	292	6	annual	annual	ADJ
fcis-6362	292	7	meeting	meeting	NOUN
fcis-6362	292	8	of	of	ADP
fcis-6362	292	9	the	the	DET
fcis-6362	292	10	association	association	NOUN
fcis-6362	292	11	for	for	ADP
fcis-6362	292	12	computational	computational	ADJ
fcis-6362	292	13	linguistics	linguistic	NOUN
fcis-6362	292	14	and	and	CCONJ
fcis-6362	292	15	the	the	DET
fcis-6362	292	16	11th	11th	ADJ
fcis-6362	292	17	international	international	ADJ
fcis-6362	292	18	joint	joint	ADJ
fcis-6362	292	19	conference	conference	NOUN
fcis-6362	292	20	on	on	ADP
fcis-6362	292	21	natural	natural	ADJ
fcis-6362	292	22	language	language	NOUN
fcis-6362	292	23	processing	processing	NOUN
fcis-6362	292	24	(	(	PUNCT
fcis-6362	292	25	volume	volume	NOUN
fcis-6362	292	26	1	1	NUM
fcis-6362	292	27	:	:	PUNCT
fcis-6362	292	28	long	long	ADJ
fcis-6362	292	29	papers	paper	NOUN
fcis-6362	292	30	)	)	PUNCT
fcis-6362	292	31	(	(	PUNCT
fcis-6362	292	32	pp	pp	X
fcis-6362	292	33	.	.	PUNCT
fcis-6362	292	34	4582	4582	NUM
fcis-6362	292	35	-	-	SYM
fcis-6362	292	36	4597	4597	NUM
fcis-6362	292	37	)	)	PUNCT
fcis-6362	292	38	.	.	PUNCT
fcis-6362	293	1	[	[	X
fcis-6362	293	2	12	12	NUM
fcis-6362	293	3	]	]	X
fcis-6362	293	4	izacard	izacard	NOUN
fcis-6362	293	5	,	,	PUNCT
fcis-6362	293	6	g.	g.	PROPN
fcis-6362	293	7	,	,	PUNCT
fcis-6362	293	8	lewis	lewis	PROPN
fcis-6362	293	9	,	,	PUNCT
fcis-6362	293	10	p.	p.	PROPN
fcis-6362	293	11	,	,	PUNCT
fcis-6362	293	12	lomeli	lomeli	PROPN
fcis-6362	293	13	,	,	PUNCT
fcis-6362	293	14	m.	m.	NOUN
fcis-6362	293	15	,	,	PUNCT
fcis-6362	293	16	hosseini	hosseini	PROPN
fcis-6362	293	17	,	,	PUNCT
fcis-6362	293	18	l.	l.	PROPN
fcis-6362	293	19	,	,	PUNCT
fcis-6362	293	20	petroni	petroni	NOUN
fcis-6362	293	21	,	,	PUNCT
fcis-6362	293	22	f.	f.	PROPN
fcis-6362	293	23	,	,	PUNCT
fcis-6362	293	24	schick	schick	PROPN
fcis-6362	293	25	,	,	PUNCT
fcis-6362	293	26	t.	t.	PROPN
fcis-6362	293	27	,	,	PUNCT
fcis-6362	293	28	...	...	PUNCT
fcis-6362	293	29	&	&	CCONJ
fcis-6362	293	30	grave	grave	PROPN
fcis-6362	293	31	,	,	PUNCT
fcis-6362	293	32	e.	e.	PROPN
fcis-6362	293	33	(	(	PUNCT
fcis-6362	293	34	2022	2022	NUM
fcis-6362	293	35	)	)	PUNCT
fcis-6362	293	36	.	.	PUNCT
fcis-6362	294	1	atlas	atlas	PROPN
fcis-6362	294	2	:	:	PUNCT
fcis-6362	294	3	few	few	ADJ
fcis-6362	294	4	-	-	PUNCT
fcis-6362	294	5	shot	shot	NOUN
fcis-6362	294	6	learning	learning	NOUN
fcis-6362	294	7	with	with	ADP
fcis-6362	294	8	retrieval	retrieval	NOUN
fcis-6362	294	9	augmented	augment	VERB
fcis-6362	294	10	language	language	NOUN
fcis-6362	294	11	models	model	NOUN
fcis-6362	294	12	.	.	PUNCT
fcis-6362	295	1	arxiv	arxiv	PROPN
fcis-6362	295	2	preprint	preprint	PROPN
fcis-6362	295	3	arxiv	arxiv	PROPN
fcis-6362	295	4	,	,	PUNCT
fcis-6362	295	5	2208	2208	NUM
fcis-6362	295	6	.	.	PUNCT
fcis-6362	296	1	[	[	X
fcis-6362	296	2	13	13	NUM
fcis-6362	296	3	]	]	X
fcis-6362	296	4	kojima	kojima	PROPN
fcis-6362	296	5	,	,	PUNCT
fcis-6362	296	6	t.	t.	PROPN
fcis-6362	296	7	,	,	PUNCT
fcis-6362	296	8	gu	gu	PROPN
fcis-6362	296	9	,	,	PUNCT
fcis-6362	296	10	s.	s.	PROPN
fcis-6362	296	11	s.	s.	PROPN
fcis-6362	296	12	,	,	PUNCT
fcis-6362	296	13	reid	reid	PROPN
fcis-6362	296	14	,	,	PUNCT
fcis-6362	296	15	m.	m.	NOUN
fcis-6362	296	16	,	,	PUNCT
fcis-6362	296	17	matsuo	matsuo	PROPN
fcis-6362	296	18	,	,	PUNCT
fcis-6362	296	19	y.	y.	PROPN
fcis-6362	296	20	,	,	PUNCT
fcis-6362	296	21	&	&	CCONJ
fcis-6362	296	22	iwasawa	iwasawa	PROPN
fcis-6362	296	23	,	,	PUNCT
fcis-6362	296	24	y.	y.	PROPN
fcis-6362	296	25	large	large	ADJ
fcis-6362	296	26	language	language	NOUN
fcis-6362	296	27	models	model	NOUN
fcis-6362	296	28	are	be	AUX
fcis-6362	296	29	zero	zero	NUM
fcis-6362	296	30	-	-	PUNCT
fcis-6362	296	31	shot	shot	NOUN
fcis-6362	296	32	reasoners	reasoner	NOUN
fcis-6362	296	33	.	.	PUNCT
fcis-6362	297	1	in	in	ADP
fcis-6362	297	2	icml	icml	NOUN
fcis-6362	297	3	2022	2022	NUM
fcis-6362	297	4	workshop	workshop	NOUN
fcis-6362	297	5	on	on	ADP
fcis-6362	297	6	knowledge	knowledge	NOUN
fcis-6362	297	7	retrieval	retrieval	NOUN
fcis-6362	297	8	and	and	CCONJ
fcis-6362	297	9	language	language	NOUN
fcis-6362	297	10	models	model	NOUN
fcis-6362	297	11	.	.	PUNCT
fcis-6362	298	1	[	[	X
fcis-6362	298	2	14	14	NUM
fcis-6362	298	3	]	]	X
fcis-6362	298	4	schick	schick	NOUN
fcis-6362	298	5	,	,	PUNCT
fcis-6362	298	6	t.	t.	PROPN
fcis-6362	298	7	,	,	PUNCT
fcis-6362	298	8	&	&	CCONJ
fcis-6362	298	9	schütze	schütze	PROPN
fcis-6362	298	10	,	,	PUNCT
fcis-6362	298	11	h.	h.	PROPN
fcis-6362	298	12	(	(	PUNCT
fcis-6362	298	13	2021	2021	NUM
fcis-6362	298	14	,	,	PUNCT
fcis-6362	298	15	april	april	PROPN
fcis-6362	298	16	)	)	PUNCT
fcis-6362	298	17	.	.	PUNCT
fcis-6362	299	1	exploiting	exploit	VERB
fcis-6362	299	2	clozequestions	clozequestion	NOUN
fcis-6362	299	3	for	for	ADP
fcis-6362	299	4	few	few	ADJ
fcis-6362	299	5	-	-	PUNCT
fcis-6362	299	6	shot	shot	NOUN
fcis-6362	299	7	text	text	NOUN
fcis-6362	299	8	classification	classification	NOUN
fcis-6362	299	9	and	and	CCONJ
fcis-6362	299	10	natural	natural	ADJ
fcis-6362	299	11	language	language	NOUN
fcis-6362	299	12	inference	inference	NOUN
fcis-6362	299	13	.	.	PUNCT
fcis-6362	300	1	in	in	ADP
fcis-6362	300	2	proceedings	proceeding	NOUN
fcis-6362	300	3	of	of	ADP
fcis-6362	300	4	the	the	DET
fcis-6362	300	5	16th	16th	ADJ
fcis-6362	300	6	conference	conference	NOUN
fcis-6362	300	7	of	of	ADP
fcis-6362	300	8	the	the	DET
fcis-6362	300	9	european	european	ADJ
fcis-6362	300	10	chapter	chapter	NOUN
fcis-6362	300	11	of	of	ADP
fcis-6362	300	12	the	the	DET
fcis-6362	300	13	association	association	NOUN
fcis-6362	300	14	for	for	ADP
fcis-6362	300	15	computational	computational	ADJ
fcis-6362	300	16	linguistics	linguistic	NOUN
fcis-6362	300	17	:	:	PUNCT
fcis-6362	300	18	main	main	ADJ
fcis-6362	300	19	volume	volume	NOUN
fcis-6362	300	20	(	(	PUNCT
fcis-6362	300	21	pp	pp	ADJ
fcis-6362	300	22	.	.	PUNCT
fcis-6362	300	23	255	255	NUM
fcis-6362	300	24	-	-	SYM
fcis-6362	300	25	269	269	NUM
fcis-6362	300	26	)	)	PUNCT
fcis-6362	300	27	.	.	PUNCT
fcis-6362	301	1	[	[	X
fcis-6362	301	2	15	15	NUM
fcis-6362	301	3	]	]	X
fcis-6362	301	4	gao	gao	PROPN
fcis-6362	301	5	,	,	PUNCT
fcis-6362	301	6	t.	t.	PROPN
fcis-6362	301	7	,	,	PUNCT
fcis-6362	301	8	fisch	fisch	PROPN
fcis-6362	301	9	,	,	PUNCT
fcis-6362	301	10	a.	a.	PROPN
fcis-6362	301	11	,	,	PUNCT
fcis-6362	301	12	&	&	CCONJ
fcis-6362	301	13	chen	chen	PROPN
fcis-6362	301	14	,	,	PUNCT
fcis-6362	301	15	d.	d.	PROPN
fcis-6362	301	16	(	(	PUNCT
fcis-6362	301	17	2021	2021	NUM
fcis-6362	301	18	,	,	PUNCT
fcis-6362	301	19	august	august	PROPN
fcis-6362	301	20	)	)	PUNCT
fcis-6362	301	21	.	.	PUNCT
fcis-6362	302	1	making	make	VERB
fcis-6362	302	2	pretrained	pretraine	VERB
fcis-6362	302	3	language	language	NOUN
fcis-6362	302	4	models	model	NOUN
fcis-6362	302	5	better	well	ADJ
fcis-6362	302	6	few	few	ADJ
fcis-6362	302	7	-	-	PUNCT
fcis-6362	302	8	shot	shot	NOUN
fcis-6362	302	9	learners	learner	NOUN
fcis-6362	302	10	.	.	PUNCT
fcis-6362	303	1	in	in	ADP
fcis-6362	303	2	proceedings	proceeding	NOUN
fcis-6362	303	3	of	of	ADP
fcis-6362	303	4	the	the	DET
fcis-6362	303	5	59th	59th	ADJ
fcis-6362	303	6	annual	annual	ADJ
fcis-6362	303	7	meeting	meeting	NOUN
fcis-6362	303	8	of	of	ADP
fcis-6362	303	9	the	the	DET
fcis-6362	303	10	association	association	NOUN
fcis-6362	303	11	for	for	ADP
fcis-6362	303	12	computational	computational	ADJ
fcis-6362	303	13	linguistics	linguistic	NOUN
fcis-6362	303	14	and	and	CCONJ
fcis-6362	303	15	the	the	DET
fcis-6362	303	16	11th	11th	ADJ
fcis-6362	303	17	international	international	ADJ
fcis-6362	303	18	joint	joint	ADJ
fcis-6362	303	19	conference	conference	NOUN
fcis-6362	303	20	on	on	ADP
fcis-6362	303	21	natural	natural	ADJ
fcis-6362	303	22	language	language	NOUN
fcis-6362	303	23	processing	processing	NOUN
fcis-6362	303	24	(	(	PUNCT
fcis-6362	303	25	volume	volume	NOUN
fcis-6362	303	26	1	1	NUM
fcis-6362	303	27	:	:	PUNCT
fcis-6362	303	28	long	long	ADJ
fcis-6362	303	29	papers	paper	NOUN
fcis-6362	303	30	)	)	PUNCT
fcis-6362	303	31	(	(	PUNCT
fcis-6362	303	32	pp	pp	ADJ
fcis-6362	303	33	.	.	PUNCT
fcis-6362	304	1	3816	3816	NUM
fcis-6362	304	2	-	-	SYM
fcis-6362	304	3	3830	3830	NUM
fcis-6362	304	4	)	)	PUNCT
fcis-6362	304	5	.	.	PUNCT
fcis-6362	305	1	[	[	X
fcis-6362	305	2	16	16	NUM
fcis-6362	305	3	]	]	PUNCT
fcis-6362	305	4	shin	shin	NOUN
fcis-6362	305	5	,	,	PUNCT
fcis-6362	305	6	t.	t.	PROPN
fcis-6362	305	7	,	,	PUNCT
fcis-6362	305	8	razeghi	razeghi	PROPN
fcis-6362	305	9	,	,	PUNCT
fcis-6362	305	10	y.	y.	PROPN
fcis-6362	305	11	,	,	PUNCT
fcis-6362	305	12	logan	logan	PROPN
fcis-6362	305	13	iv	iv	NUM
fcis-6362	305	14	,	,	PUNCT
fcis-6362	305	15	r.	r.	PROPN
fcis-6362	305	16	l.	l.	PROPN
fcis-6362	305	17	,	,	PUNCT
fcis-6362	305	18	wallace	wallace	PROPN
fcis-6362	305	19	,	,	PUNCT
fcis-6362	305	20	e.	e.	PROPN
fcis-6362	305	21	,	,	PUNCT
fcis-6362	305	22	&	&	CCONJ
fcis-6362	305	23	singh	singh	PROPN
fcis-6362	305	24	,	,	PUNCT
fcis-6362	305	25	s.	s.	PROPN
fcis-6362	305	26	(	(	PUNCT
fcis-6362	305	27	2020	2020	NUM
fcis-6362	305	28	,	,	PUNCT
fcis-6362	305	29	november	november	PROPN
fcis-6362	305	30	)	)	PUNCT
fcis-6362	305	31	.	.	PUNCT
fcis-6362	306	1	autoprompt	autoprompt	NOUN
fcis-6362	306	2	:	:	PUNCT
fcis-6362	306	3	eliciting	elicit	VERB
fcis-6362	306	4	knowledge	knowledge	NOUN
fcis-6362	306	5	from	from	ADP
fcis-6362	306	6	language	language	NOUN
fcis-6362	306	7	models	model	NOUN
fcis-6362	306	8	with	with	ADP
fcis-6362	306	9	automatically	automatically	ADV
fcis-6362	306	10	generated	generate	VERB
fcis-6362	306	11	prompts	prompt	NOUN
fcis-6362	306	12	.	.	PUNCT
fcis-6362	307	1	in	in	ADP
fcis-6362	307	2	proceedings	proceeding	NOUN
fcis-6362	307	3	of	of	ADP
fcis-6362	307	4	the	the	DET
fcis-6362	307	5	2020	2020	NUM
fcis-6362	307	6	conference	conference	NOUN
fcis-6362	307	7	on	on	ADP
fcis-6362	307	8	empirical	empirical	ADJ
fcis-6362	307	9	methods	method	NOUN
fcis-6362	307	10	in	in	ADP
fcis-6362	307	11	natural	natural	ADJ
fcis-6362	307	12	language	language	NOUN
fcis-6362	307	13	processing	processing	NOUN
fcis-6362	307	14	(	(	PUNCT
fcis-6362	307	15	emnlp	emnlp	ADJ
fcis-6362	307	16	)	)	PUNCT
fcis-6362	307	17	(	(	PUNCT
fcis-6362	307	18	pp	pp	ADJ
fcis-6362	307	19	.	.	PUNCT
fcis-6362	308	1	4222	4222	NUM
fcis-6362	308	2	-	-	SYM
fcis-6362	308	3	4235	4235	NUM
fcis-6362	308	4	)	)	PUNCT
fcis-6362	308	5	.	.	PUNCT
fcis-6362	309	1	172	172	NUM
fcis-6362	310	1	[	[	X
fcis-6362	310	2	17	17	NUM
fcis-6362	310	3	]	]	X
fcis-6362	310	4	liu	liu	PROPN
fcis-6362	310	5	,	,	PUNCT
fcis-6362	310	6	x.	x.	PROPN
fcis-6362	310	7	,	,	PUNCT
fcis-6362	310	8	ji	ji	PROPN
fcis-6362	310	9	,	,	PUNCT
fcis-6362	310	10	k.	k.	PROPN
fcis-6362	310	11	,	,	PUNCT
fcis-6362	310	12	fu	fu	PROPN
fcis-6362	310	13	,	,	PUNCT
fcis-6362	310	14	y.	y.	PROPN
fcis-6362	310	15	,	,	PUNCT
fcis-6362	310	16	tam	tam	PROPN
fcis-6362	310	17	,	,	PUNCT
fcis-6362	310	18	w.	w.	PROPN
fcis-6362	310	19	,	,	PUNCT
fcis-6362	310	20	du	du	PROPN
fcis-6362	310	21	,	,	PUNCT
fcis-6362	310	22	z.	z.	PROPN
fcis-6362	310	23	,	,	PUNCT
fcis-6362	310	24	yang	yang	PROPN
fcis-6362	310	25	,	,	PUNCT
fcis-6362	310	26	z.	z.	PROPN
fcis-6362	310	27	,	,	PUNCT
fcis-6362	310	28	&	&	CCONJ
fcis-6362	310	29	tang	tang	PROPN
fcis-6362	310	30	,	,	PUNCT
fcis-6362	310	31	j.	j.	PROPN
fcis-6362	310	32	(	(	PUNCT
fcis-6362	310	33	2022	2022	NUM
fcis-6362	310	34	,	,	PUNCT
fcis-6362	310	35	may	may	AUX
fcis-6362	310	36	)	)	PUNCT
fcis-6362	310	37	.	.	PUNCT
fcis-6362	311	1	p	p	X
fcis-6362	311	2	-	-	PUNCT
fcis-6362	311	3	tuning	tuning	NOUN
fcis-6362	311	4	:	:	PUNCT
fcis-6362	311	5	prompt	prompt	ADJ
fcis-6362	311	6	tuning	tuning	NOUN
fcis-6362	311	7	can	can	AUX
fcis-6362	311	8	be	be	AUX
fcis-6362	311	9	comparable	comparable	ADJ
fcis-6362	311	10	to	to	ADP
fcis-6362	311	11	fine	fine	ADV
fcis-6362	311	12	-	-	PUNCT
fcis-6362	311	13	tuning	tuning	NOUN
fcis-6362	311	14	across	across	ADP
fcis-6362	311	15	scales	scale	NOUN
fcis-6362	311	16	and	and	CCONJ
fcis-6362	311	17	tasks	task	NOUN
fcis-6362	311	18	.	.	PUNCT
fcis-6362	312	1	in	in	ADP
fcis-6362	312	2	proceedings	proceeding	NOUN
fcis-6362	312	3	of	of	ADP
fcis-6362	312	4	the	the	DET
fcis-6362	312	5	60th	60th	ADJ
fcis-6362	312	6	annual	annual	ADJ
fcis-6362	312	7	meeting	meeting	NOUN
fcis-6362	312	8	of	of	ADP
fcis-6362	312	9	the	the	DET
fcis-6362	312	10	association	association	NOUN
fcis-6362	312	11	for	for	ADP
fcis-6362	312	12	computational	computational	ADJ
fcis-6362	312	13	linguistics	linguistic	NOUN
fcis-6362	312	14	(	(	PUNCT
fcis-6362	312	15	volume	volume	NOUN
fcis-6362	312	16	2	2	NUM
fcis-6362	312	17	:	:	PUNCT
fcis-6362	312	18	short	short	ADJ
fcis-6362	312	19	papers	paper	NOUN
fcis-6362	312	20	)	)	PUNCT
fcis-6362	312	21	(	(	PUNCT
fcis-6362	312	22	pp	pp	X
fcis-6362	312	23	.	.	PUNCT
fcis-6362	313	1	61	61	NUM
fcis-6362	313	2	-	-	SYM
fcis-6362	313	3	68	68	NUM
fcis-6362	313	4	)	)	PUNCT
fcis-6362	313	5	.	.	PUNCT
fcis-6362	314	1	[	[	X
fcis-6362	314	2	18	18	NUM
fcis-6362	314	3	]	]	SYM
fcis-6362	314	4	yin	yin	PROPN
fcis-6362	314	5	,	,	PUNCT
fcis-6362	314	6	w.	w.	PROPN
fcis-6362	314	7	,	,	PUNCT
fcis-6362	314	8	hay	hay	PROPN
fcis-6362	314	9	,	,	PUNCT
fcis-6362	314	10	j.	j.	PROPN
fcis-6362	314	11	,	,	PUNCT
fcis-6362	314	12	&	&	CCONJ
fcis-6362	314	13	roth	roth	PROPN
fcis-6362	314	14	,	,	PUNCT
fcis-6362	314	15	d.	d.	PROPN
fcis-6362	314	16	(	(	PUNCT
fcis-6362	314	17	2019	2019	NUM
fcis-6362	314	18	,	,	PUNCT
fcis-6362	314	19	november	november	PROPN
fcis-6362	314	20	)	)	PUNCT
fcis-6362	314	21	.	.	PUNCT
fcis-6362	315	1	benchmarking	benchmarke	VERB
fcis-6362	315	2	zero	zero	NUM
fcis-6362	315	3	-	-	PUNCT
fcis-6362	315	4	shot	shot	NOUN
fcis-6362	315	5	text	text	NOUN
fcis-6362	315	6	classification	classification	NOUN
fcis-6362	315	7	:	:	PUNCT
fcis-6362	315	8	datasets	dataset	NOUN
fcis-6362	315	9	,	,	PUNCT
fcis-6362	315	10	evaluation	evaluation	NOUN
fcis-6362	315	11	and	and	CCONJ
fcis-6362	315	12	entailment	entailment	ADJ
fcis-6362	315	13	approach	approach	NOUN
fcis-6362	315	14	.	.	PUNCT
fcis-6362	316	1	in	in	ADP
fcis-6362	316	2	proceedings	proceeding	NOUN
fcis-6362	316	3	of	of	ADP
fcis-6362	316	4	the	the	DET
fcis-6362	316	5	2019	2019	NUM
fcis-6362	316	6	conference	conference	NOUN
fcis-6362	316	7	on	on	ADP
fcis-6362	316	8	empirical	empirical	ADJ
fcis-6362	316	9	methods	method	NOUN
fcis-6362	316	10	in	in	ADP
fcis-6362	316	11	natural	natural	ADJ
fcis-6362	316	12	language	language	NOUN
fcis-6362	316	13	processing	processing	NOUN
fcis-6362	316	14	and	and	CCONJ
fcis-6362	316	15	the	the	DET
fcis-6362	316	16	9th	9th	ADJ
fcis-6362	316	17	international	international	ADJ
fcis-6362	316	18	joint	joint	ADJ
fcis-6362	316	19	conference	conference	NOUN
fcis-6362	316	20	on	on	ADP
fcis-6362	316	21	natural	natural	ADJ
fcis-6362	316	22	language	language	NOUN
fcis-6362	316	23	processing	processing	NOUN
fcis-6362	316	24	(	(	PUNCT
fcis-6362	316	25	emnlp	emnlp	NOUN
fcis-6362	316	26	-	-	PUNCT
fcis-6362	316	27	ijcnlp	ijcnlp	NOUN
fcis-6362	316	28	)	)	PUNCT
fcis-6362	316	29	(	(	PUNCT
fcis-6362	316	30	pp	pp	ADP
fcis-6362	316	31	.	.	PUNCT
fcis-6362	317	1	3914	3914	NUM
fcis-6362	317	2	-	-	SYM
fcis-6362	317	3	3923	3923	NUM
fcis-6362	317	4	)	)	PUNCT
fcis-6362	317	5	..	..	PUNCT
fcis-6362	318	1	[	[	X
fcis-6362	318	2	19	19	NUM
fcis-6362	318	3	]	]	X
fcis-6362	318	4	chen	chen	PROPN
fcis-6362	318	5	,	,	PUNCT
fcis-6362	318	6	x.	x.	PROPN
fcis-6362	318	7	,	,	PUNCT
fcis-6362	318	8	zhang	zhang	PROPN
fcis-6362	318	9	,	,	PUNCT
fcis-6362	318	10	n.	n.	PROPN
fcis-6362	318	11	,	,	PUNCT
fcis-6362	318	12	xie	xie	PROPN
fcis-6362	318	13	,	,	PUNCT
fcis-6362	318	14	x.	x.	PROPN
fcis-6362	318	15	,	,	PUNCT
fcis-6362	318	16	deng	deng	PROPN
fcis-6362	318	17	,	,	PUNCT
fcis-6362	318	18	s.	s.	PROPN
fcis-6362	318	19	,	,	PUNCT
fcis-6362	318	20	yao	yao	PROPN
fcis-6362	318	21	,	,	PUNCT
fcis-6362	318	22	y.	y.	PROPN
fcis-6362	318	23	,	,	PUNCT
fcis-6362	318	24	tan	tan	PROPN
fcis-6362	318	25	,	,	PUNCT
fcis-6362	318	26	c.	c.	PROPN
fcis-6362	318	27	,	,	PUNCT
fcis-6362	318	28	...	...	PUNCT
fcis-6362	318	29	&	&	CCONJ
fcis-6362	318	30	chen	chen	PROPN
fcis-6362	318	31	,	,	PUNCT
fcis-6362	318	32	h.	h.	PROPN
fcis-6362	318	33	(	(	PUNCT
fcis-6362	318	34	2022	2022	NUM
fcis-6362	318	35	,	,	PUNCT
fcis-6362	318	36	april	april	PROPN
fcis-6362	318	37	)	)	PUNCT
fcis-6362	318	38	.	.	PUNCT
fcis-6362	319	1	knowprompt	knowprompt	ADJ
fcis-6362	319	2	:	:	PUNCT
fcis-6362	319	3	knowledge	knowledge	NOUN
fcis-6362	319	4	-	-	PUNCT
fcis-6362	319	5	aware	aware	ADJ
fcis-6362	319	6	prompt	prompt	NOUN
fcis-6362	319	7	-	-	PUNCT
fcis-6362	319	8	tuning	tuning	NOUN
fcis-6362	319	9	with	with	ADP
fcis-6362	319	10	synergistic	synergistic	ADJ
fcis-6362	319	11	optimization	optimization	NOUN
fcis-6362	319	12	for	for	ADP
fcis-6362	319	13	relation	relation	NOUN
fcis-6362	319	14	extraction	extraction	NOUN
fcis-6362	319	15	.	.	PUNCT
fcis-6362	320	1	in	in	ADP
fcis-6362	320	2	proceedings	proceeding	NOUN
fcis-6362	320	3	of	of	ADP
fcis-6362	320	4	the	the	DET
fcis-6362	320	5	acm	acm	PROPN
fcis-6362	320	6	web	web	NOUN
fcis-6362	320	7	conference	conference	NOUN
fcis-6362	320	8	2022	2022	NUM
fcis-6362	320	9	(	(	PUNCT
fcis-6362	320	10	pp	pp	ADJ
fcis-6362	320	11	.	.	PUNCT
fcis-6362	321	1	2778	2778	NUM
fcis-6362	321	2	-	-	SYM
fcis-6362	321	3	2788	2788	NUM
fcis-6362	321	4	)	)	PUNCT
fcis-6362	321	5	.	.	PUNCT
fcis-6362	322	1	[	[	X
fcis-6362	322	2	20	20	NUM
fcis-6362	322	3	]	]	PUNCT
fcis-6362	322	4	hambardzumyan	hambardzumyan	PROPN
fcis-6362	322	5	,	,	PUNCT
fcis-6362	322	6	k.	k.	PROPN
fcis-6362	322	7	,	,	PUNCT
fcis-6362	322	8	khachatrian	khachatrian	PROPN
fcis-6362	322	9	,	,	PUNCT
fcis-6362	322	10	h.	h.	PROPN
fcis-6362	322	11	,	,	PUNCT
fcis-6362	322	12	&	&	CCONJ
fcis-6362	322	13	may	may	AUX
fcis-6362	322	14	,	,	PUNCT
fcis-6362	322	15	j.	j.	PROPN
fcis-6362	322	16	(	(	PUNCT
fcis-6362	322	17	2021	2021	NUM
fcis-6362	322	18	,	,	PUNCT
fcis-6362	322	19	august	august	PROPN
fcis-6362	322	20	)	)	PUNCT
fcis-6362	322	21	.	.	PUNCT
fcis-6362	323	1	warp	warp	NOUN
fcis-6362	323	2	:	:	PUNCT
fcis-6362	323	3	word	word	NOUN
fcis-6362	323	4	-	-	PUNCT
fcis-6362	323	5	level	level	NOUN
fcis-6362	323	6	adversarial	adversarial	ADJ
fcis-6362	323	7	reprogramming	reprogramming	NOUN
fcis-6362	323	8	.	.	PUNCT
fcis-6362	324	1	in	in	ADP
fcis-6362	324	2	proceedings	proceeding	NOUN
fcis-6362	324	3	of	of	ADP
fcis-6362	324	4	the	the	DET
fcis-6362	324	5	59th	59th	ADJ
fcis-6362	324	6	annual	annual	ADJ
fcis-6362	324	7	meeting	meeting	NOUN
fcis-6362	324	8	of	of	ADP
fcis-6362	324	9	the	the	DET
fcis-6362	324	10	association	association	NOUN
fcis-6362	324	11	for	for	ADP
fcis-6362	324	12	computational	computational	ADJ
fcis-6362	324	13	linguistics	linguistic	NOUN
fcis-6362	324	14	and	and	CCONJ
fcis-6362	324	15	the	the	DET
fcis-6362	324	16	11th	11th	ADJ
fcis-6362	324	17	international	international	ADJ
fcis-6362	324	18	joint	joint	ADJ
fcis-6362	324	19	conference	conference	NOUN
fcis-6362	324	20	on	on	ADP
fcis-6362	324	21	natural	natural	ADJ
fcis-6362	324	22	language	language	NOUN
fcis-6362	324	23	processing	processing	NOUN
fcis-6362	324	24	(	(	PUNCT
fcis-6362	324	25	volume	volume	NOUN
fcis-6362	324	26	1	1	NUM
fcis-6362	324	27	:	:	PUNCT
fcis-6362	324	28	long	long	ADJ
fcis-6362	324	29	papers	paper	NOUN
fcis-6362	324	30	)	)	PUNCT
fcis-6362	324	31	(	(	PUNCT
fcis-6362	324	32	pp	pp	ADP
fcis-6362	324	33	.	.	PUNCT
fcis-6362	324	34	4921	4921	NUM
fcis-6362	324	35	-	-	SYM
fcis-6362	324	36	4933	4933	NUM
fcis-6362	324	37	)	)	PUNCT
fcis-6362	324	38	.	.	PUNCT
fcis-6362	325	1	[	[	X
fcis-6362	325	2	21	21	NUM
fcis-6362	325	3	]	]	X
fcis-6362	325	4	liu	liu	PROPN
fcis-6362	325	5	,	,	PUNCT
fcis-6362	325	6	x.	x.	PROPN
fcis-6362	325	7	,	,	PUNCT
fcis-6362	325	8	zheng	zheng	PROPN
fcis-6362	325	9	,	,	PUNCT
fcis-6362	325	10	y.	y.	PROPN
fcis-6362	325	11	,	,	PUNCT
fcis-6362	325	12	du	du	PROPN
fcis-6362	325	13	,	,	PUNCT
fcis-6362	325	14	z.	z.	PROPN
fcis-6362	325	15	,	,	PUNCT
fcis-6362	325	16	ding	ding	NOUN
fcis-6362	325	17	,	,	PUNCT
fcis-6362	325	18	m.	m.	NOUN
fcis-6362	325	19	,	,	PUNCT
fcis-6362	325	20	qian	qian	PROPN
fcis-6362	325	21	,	,	PUNCT
fcis-6362	325	22	y.	y.	PROPN
fcis-6362	325	23	,	,	PUNCT
fcis-6362	325	24	yang	yang	PROPN
fcis-6362	325	25	,	,	PUNCT
fcis-6362	325	26	z.	z.	PROPN
fcis-6362	325	27	,	,	PUNCT
fcis-6362	325	28	&	&	CCONJ
fcis-6362	325	29	tang	tang	PROPN
fcis-6362	325	30	,	,	PUNCT
fcis-6362	325	31	j.	j.	PROPN
fcis-6362	325	32	(	(	PUNCT
fcis-6362	325	33	2021	2021	NUM
fcis-6362	325	34	)	)	PUNCT
fcis-6362	325	35	.	.	PUNCT
fcis-6362	326	1	gpt	gpt	PROPN
fcis-6362	326	2	understands	understand	VERB
fcis-6362	326	3	,	,	PUNCT
fcis-6362	326	4	too	too	ADV
fcis-6362	326	5	.	.	PUNCT
fcis-6362	327	1	arxiv	arxiv	PROPN
fcis-6362	327	2	preprint	preprint	PROPN
fcis-6362	327	3	arxiv:2103.10385	arxiv:2103.10385	PROPN
fcis-6362	327	4	.	.	PUNCT
fcis-6362	328	1	[	[	X
fcis-6362	328	2	22	22	NUM
fcis-6362	328	3	]	]	PUNCT
fcis-6362	328	4	raffel	raffel	NOUN
fcis-6362	328	5	,	,	PUNCT
fcis-6362	328	6	c.	c.	NOUN
fcis-6362	328	7	,	,	PUNCT
fcis-6362	328	8	shazeer	shazeer	NOUN
fcis-6362	328	9	,	,	PUNCT
fcis-6362	328	10	n.	n.	NOUN
fcis-6362	328	11	,	,	PUNCT
fcis-6362	328	12	roberts	roberts	PROPN
fcis-6362	328	13	,	,	PUNCT
fcis-6362	328	14	a.	a.	PROPN
fcis-6362	328	15	,	,	PUNCT
fcis-6362	328	16	lee	lee	PROPN
fcis-6362	328	17	,	,	PUNCT
fcis-6362	328	18	k.	k.	PROPN
fcis-6362	328	19	,	,	PUNCT
fcis-6362	328	20	narang	narang	PROPN
fcis-6362	328	21	,	,	PUNCT
fcis-6362	328	22	s.	s.	PROPN
fcis-6362	328	23	,	,	PUNCT
fcis-6362	328	24	matena	matena	PROPN
fcis-6362	328	25	,	,	PUNCT
fcis-6362	328	26	m.	m.	NOUN
fcis-6362	328	27	,	,	PUNCT
fcis-6362	328	28	...	...	PUNCT
fcis-6362	328	29	&	&	CCONJ
fcis-6362	328	30	liu	liu	PROPN
fcis-6362	328	31	,	,	PUNCT
fcis-6362	328	32	p.	p.	PROPN
fcis-6362	328	33	j.	j.	PROPN
fcis-6362	328	34	(	(	PUNCT
fcis-6362	328	35	2020	2020	NUM
fcis-6362	328	36	)	)	PUNCT
fcis-6362	328	37	.	.	PUNCT
fcis-6362	329	1	exploring	explore	VERB
fcis-6362	329	2	the	the	DET
fcis-6362	329	3	limits	limit	NOUN
fcis-6362	329	4	of	of	ADP
fcis-6362	329	5	transfer	transfer	NOUN
fcis-6362	329	6	learning	learn	VERB
fcis-6362	329	7	with	with	ADP
fcis-6362	329	8	a	a	DET
fcis-6362	329	9	unified	unified	ADJ
fcis-6362	329	10	text	text	NOUN
fcis-6362	329	11	-	-	PUNCT
fcis-6362	329	12	to	to	ADP
fcis-6362	329	13	-	-	PUNCT
fcis-6362	329	14	text	text	NOUN
fcis-6362	329	15	transformer	transformer	NOUN
fcis-6362	329	16	.	.	PUNCT
fcis-6362	330	1	the	the	DET
fcis-6362	330	2	journal	journal	NOUN
fcis-6362	330	3	of	of	ADP
fcis-6362	330	4	machine	machine	NOUN
fcis-6362	330	5	learning	learn	VERB
fcis-6362	330	6	research	research	NOUN
fcis-6362	330	7	,	,	PUNCT
fcis-6362	330	8	21(1	21(1	NUM
fcis-6362	330	9	)	)	PUNCT
fcis-6362	330	10	,	,	PUNCT
fcis-6362	330	11	5485	5485	NUM
fcis-6362	330	12	-	-	SYM
fcis-6362	330	13	5551	5551	NUM
fcis-6362	330	14	.	.	PUNCT
fcis-6362	331	1	[	[	X
fcis-6362	331	2	23	23	NUM
fcis-6362	331	3	]	]	X
fcis-6362	331	4	kingma	kingma	PROPN
fcis-6362	331	5	,	,	PUNCT
fcis-6362	331	6	d.	d.	PROPN
fcis-6362	331	7	p.	p.	PROPN
fcis-6362	331	8	,	,	PUNCT
fcis-6362	331	9	&	&	CCONJ
fcis-6362	331	10	welling	well	VERB
fcis-6362	331	11	,	,	PUNCT
fcis-6362	331	12	m.	m.	NOUN
fcis-6362	331	13	(	(	PUNCT
fcis-6362	331	14	2013	2013	NUM
fcis-6362	331	15	)	)	PUNCT
fcis-6362	331	16	.	.	PUNCT
fcis-6362	332	1	auto	auto	NOUN
fcis-6362	332	2	-	-	PUNCT
fcis-6362	332	3	encoding	encode	VERB
fcis-6362	332	4	variational	variational	ADJ
fcis-6362	332	5	bayes	baye	NOUN
fcis-6362	332	6	.	.	PUNCT
fcis-6362	333	1	arxiv	arxiv	PROPN
fcis-6362	333	2	preprint	preprint	NOUN
fcis-6362	333	3	arxiv:1312.6114	arxiv:1312.6114	NOUN
fcis-6362	333	4	.	.	PUNCT
fcis-6362	334	1	[	[	X
fcis-6362	334	2	24	24	NUM
fcis-6362	334	3	]	]	X
fcis-6362	334	4	zhang	zhang	PROPN
fcis-6362	334	5	,	,	PUNCT
fcis-6362	334	6	x.	x.	PROPN
fcis-6362	334	7	,	,	PUNCT
fcis-6362	334	8	zhao	zhao	PROPN
fcis-6362	334	9	,	,	PUNCT
fcis-6362	334	10	j.	j.	PROPN
fcis-6362	334	11	,	,	PUNCT
fcis-6362	334	12	&	&	CCONJ
fcis-6362	334	13	lecun	lecun	PROPN
fcis-6362	334	14	,	,	PUNCT
fcis-6362	334	15	y.	y.	PROPN
fcis-6362	334	16	(	(	PUNCT
fcis-6362	334	17	2015	2015	NUM
fcis-6362	334	18	)	)	PUNCT
fcis-6362	334	19	.	.	PUNCT
fcis-6362	335	1	character	character	NOUN
fcis-6362	335	2	-	-	PUNCT
fcis-6362	335	3	level	level	NOUN
fcis-6362	335	4	convolutional	convolutional	ADJ
fcis-6362	335	5	networks	network	NOUN
fcis-6362	335	6	for	for	ADP
fcis-6362	335	7	text	text	NOUN
fcis-6362	335	8	classification	classification	NOUN
fcis-6362	335	9	.	.	PUNCT
fcis-6362	336	1	advances	advance	NOUN
fcis-6362	336	2	in	in	ADP
fcis-6362	336	3	neural	neural	ADJ
fcis-6362	336	4	information	information	NOUN
fcis-6362	336	5	processing	processing	NOUN
fcis-6362	336	6	systems	system	NOUN
fcis-6362	336	7	,	,	PUNCT
fcis-6362	336	8	28	28	NUM
fcis-6362	336	9	.	.	PUNCT
fcis-6362	337	1	[	[	X
fcis-6362	337	2	25	25	NUM
fcis-6362	337	3	]	]	X
fcis-6362	337	4	maas	maas	PROPN
fcis-6362	337	5	,	,	PUNCT
fcis-6362	337	6	a.	a.	PROPN
fcis-6362	337	7	,	,	PUNCT
fcis-6362	337	8	daly	daly	PROPN
fcis-6362	337	9	,	,	PUNCT
fcis-6362	337	10	r.	r.	PROPN
fcis-6362	337	11	e.	e.	PROPN
fcis-6362	337	12	,	,	PUNCT
fcis-6362	337	13	pham	pham	PROPN
fcis-6362	337	14	,	,	PUNCT
fcis-6362	337	15	p.	p.	PROPN
fcis-6362	337	16	t.	t.	PROPN
fcis-6362	337	17	,	,	PUNCT
fcis-6362	337	18	huang	huang	PROPN
fcis-6362	337	19	,	,	PUNCT
fcis-6362	337	20	d.	d.	PROPN
fcis-6362	337	21	,	,	PUNCT
fcis-6362	337	22	ng	ng	PROPN
fcis-6362	337	23	,	,	PUNCT
fcis-6362	337	24	a.	a.	PROPN
fcis-6362	337	25	y.	y.	PROPN
fcis-6362	337	26	,	,	PUNCT
fcis-6362	337	27	&	&	CCONJ
fcis-6362	337	28	potts	potts	PROPN
fcis-6362	337	29	,	,	PUNCT
fcis-6362	337	30	c.	c.	PROPN
fcis-6362	337	31	(	(	PUNCT
fcis-6362	337	32	2011	2011	NUM
fcis-6362	337	33	,	,	PUNCT
fcis-6362	337	34	june	june	PROPN
fcis-6362	337	35	)	)	PUNCT
fcis-6362	337	36	.	.	PUNCT
fcis-6362	338	1	learning	learn	VERB
fcis-6362	338	2	word	word	NOUN
fcis-6362	338	3	vectors	vector	NOUN
fcis-6362	338	4	for	for	ADP
fcis-6362	338	5	sentiment	sentiment	NOUN
fcis-6362	338	6	analysis	analysis	NOUN
fcis-6362	338	7	.	.	PUNCT
fcis-6362	339	1	in	in	ADP
fcis-6362	339	2	proceedings	proceeding	NOUN
fcis-6362	339	3	of	of	ADP
fcis-6362	339	4	the	the	DET
fcis-6362	339	5	49th	49th	ADJ
fcis-6362	339	6	annual	annual	ADJ
fcis-6362	339	7	meeting	meeting	NOUN
fcis-6362	339	8	of	of	ADP
fcis-6362	339	9	the	the	DET
fcis-6362	339	10	association	association	NOUN
fcis-6362	339	11	for	for	ADP
fcis-6362	339	12	computational	computational	ADJ
fcis-6362	339	13	linguistics	linguistic	NOUN
fcis-6362	339	14	:	:	PUNCT
fcis-6362	339	15	human	human	ADJ
fcis-6362	339	16	language	language	NOUN
fcis-6362	339	17	technologies	technology	NOUN
fcis-6362	339	18	(	(	PUNCT
fcis-6362	339	19	pp	pp	ADJ
fcis-6362	339	20	.	.	PUNCT
fcis-6362	339	21	142	142	NUM
fcis-6362	339	22	-	-	SYM
fcis-6362	339	23	150	150	NUM
fcis-6362	339	24	)	)	PUNCT
fcis-6362	339	25	.	.	PUNCT
fcis-6362	340	1	[	[	X
fcis-6362	340	2	26	26	NUM
fcis-6362	340	3	]	]	X
fcis-6362	340	4	mcauley	mcauley	PROPN
fcis-6362	340	5	,	,	PUNCT
fcis-6362	340	6	j.	j.	PROPN
fcis-6362	340	7	,	,	PUNCT
fcis-6362	340	8	&	&	CCONJ
fcis-6362	340	9	leskovec	leskovec	PROPN
fcis-6362	340	10	,	,	PUNCT
fcis-6362	340	11	j.	j.	PROPN
fcis-6362	340	12	(	(	PUNCT
fcis-6362	340	13	2013	2013	NUM
fcis-6362	340	14	,	,	PUNCT
fcis-6362	340	15	october	october	PROPN
fcis-6362	340	16	)	)	PUNCT
fcis-6362	340	17	.	.	PUNCT
fcis-6362	341	1	hidden	hide	VERB
fcis-6362	341	2	factors	factor	NOUN
fcis-6362	341	3	and	and	CCONJ
fcis-6362	341	4	hidden	hidden	ADJ
fcis-6362	341	5	topics	topic	NOUN
fcis-6362	341	6	:	:	PUNCT
fcis-6362	341	7	understanding	understand	VERB
fcis-6362	341	8	rating	rating	NOUN
fcis-6362	341	9	dimensions	dimension	NOUN
fcis-6362	341	10	with	with	ADP
fcis-6362	341	11	review	review	NOUN
fcis-6362	341	12	text	text	NOUN
fcis-6362	341	13	.	.	PUNCT
fcis-6362	342	1	in	in	ADP
fcis-6362	342	2	proceedings	proceeding	NOUN
fcis-6362	342	3	of	of	ADP
fcis-6362	342	4	the	the	DET
fcis-6362	342	5	7th	7th	ADJ
fcis-6362	342	6	acm	acm	PROPN
fcis-6362	342	7	conference	conference	NOUN
fcis-6362	342	8	on	on	ADP
fcis-6362	342	9	recommender	recommender	NOUN
fcis-6362	342	10	systems	system	NOUN
fcis-6362	342	11	(	(	PUNCT
fcis-6362	342	12	pp	pp	ADJ
fcis-6362	342	13	.	.	PUNCT
fcis-6362	343	1	165	165	NUM
fcis-6362	343	2	-	-	SYM
fcis-6362	343	3	172	172	NUM
fcis-6362	343	4	)	)	PUNCT
fcis-6362	343	5	.	.	PUNCT
fcis-6362	344	1	[	[	X
fcis-6362	344	2	27	27	NUM
fcis-6362	344	3	]	]	X
fcis-6362	344	4	liu	liu	PROPN
fcis-6362	344	5	,	,	PUNCT
fcis-6362	344	6	y.	y.	PROPN
fcis-6362	344	7	,	,	PUNCT
fcis-6362	344	8	ott	ott	PROPN
fcis-6362	344	9	,	,	PUNCT
fcis-6362	344	10	m.	m.	NOUN
fcis-6362	344	11	,	,	PUNCT
fcis-6362	344	12	goyal	goyal	PROPN
fcis-6362	344	13	,	,	PUNCT
fcis-6362	344	14	n.	n.	NOUN
fcis-6362	344	15	,	,	PUNCT
fcis-6362	344	16	du	du	PROPN
fcis-6362	344	17	,	,	PUNCT
fcis-6362	344	18	j.	j.	PROPN
fcis-6362	344	19	,	,	PUNCT
fcis-6362	344	20	joshi	joshi	PROPN
fcis-6362	344	21	,	,	PUNCT
fcis-6362	344	22	m.	m.	NOUN
fcis-6362	344	23	,	,	PUNCT
fcis-6362	344	24	chen	chen	PROPN
fcis-6362	344	25	,	,	PUNCT
fcis-6362	344	26	d.	d.	PROPN
fcis-6362	344	27	,	,	PUNCT
fcis-6362	344	28	...	...	PUNCT
fcis-6362	344	29	&	&	CCONJ
fcis-6362	344	30	stoyanov	stoyanov	PROPN
fcis-6362	344	31	,	,	PUNCT
fcis-6362	344	32	v.	v.	PROPN
fcis-6362	344	33	(	(	PUNCT
fcis-6362	344	34	2019	2019	NUM
fcis-6362	344	35	)	)	PUNCT
fcis-6362	344	36	.	.	PUNCT
fcis-6362	345	1	roberta	roberta	PROPN
fcis-6362	345	2	:	:	PUNCT
fcis-6362	345	3	a	a	DET
fcis-6362	345	4	robustly	robustly	ADV
fcis-6362	345	5	optimized	optimize	VERB
fcis-6362	345	6	bert	bert	NOUN
fcis-6362	345	7	pretraining	pretraine	VERB
fcis-6362	345	8	approach	approach	NOUN
fcis-6362	345	9	.	.	PUNCT
fcis-6362	346	1	arxiv	arxiv	PROPN
fcis-6362	346	2	preprint	preprint	NOUN
fcis-6362	346	3	arxiv:1907.11692	arxiv:1907.11692	NOUN
fcis-6362	346	4	.	.	PUNCT
fcis-6362	347	1	[	[	X
fcis-6362	347	2	28	28	NUM
fcis-6362	347	3	]	]	X
fcis-6362	347	4	mcmillan	mcmillan	NOUN
fcis-6362	347	5	-	-	PUNCT
fcis-6362	347	6	major	major	PROPN
fcis-6362	347	7	,	,	PUNCT
fcis-6362	347	8	a.	a.	NOUN
fcis-6362	347	9	,	,	PUNCT
fcis-6362	347	10	osei	osei	PROPN
fcis-6362	347	11	,	,	PUNCT
fcis-6362	347	12	s.	s.	PROPN
fcis-6362	347	13	,	,	PUNCT
fcis-6362	347	14	rodriguez	rodriguez	PROPN
fcis-6362	347	15	,	,	PUNCT
fcis-6362	347	16	j.	j.	PROPN
fcis-6362	347	17	d.	d.	PROPN
fcis-6362	347	18	,	,	PUNCT
fcis-6362	347	19	ammanamanchi	ammanamanchi	PROPN
fcis-6362	347	20	,	,	PUNCT
fcis-6362	347	21	p.	p.	PROPN
fcis-6362	347	22	s.	s.	PROPN
fcis-6362	347	23	,	,	PUNCT
fcis-6362	347	24	gehrmann	gehrmann	PROPN
fcis-6362	347	25	,	,	PUNCT
fcis-6362	347	26	s.	s.	PROPN
fcis-6362	347	27	,	,	PUNCT
fcis-6362	347	28	&	&	CCONJ
fcis-6362	347	29	jernite	jernite	PROPN
fcis-6362	347	30	,	,	PUNCT
fcis-6362	347	31	y.	y.	PROPN
fcis-6362	347	32	(	(	PUNCT
fcis-6362	347	33	2021	2021	NUM
fcis-6362	347	34	)	)	PUNCT
fcis-6362	347	35	.	.	PUNCT
fcis-6362	348	1	reusable	reusable	ADJ
fcis-6362	348	2	templates	template	NOUN
fcis-6362	348	3	and	and	CCONJ
fcis-6362	348	4	guides	guide	NOUN
fcis-6362	348	5	for	for	ADP
fcis-6362	348	6	documenting	document	VERB
fcis-6362	348	7	datasets	dataset	NOUN
fcis-6362	348	8	and	and	CCONJ
fcis-6362	348	9	models	model	NOUN
fcis-6362	348	10	for	for	ADP
fcis-6362	348	11	natural	natural	ADJ
fcis-6362	348	12	language	language	NOUN
fcis-6362	348	13	processing	processing	NOUN
fcis-6362	348	14	and	and	CCONJ
fcis-6362	348	15	generation	generation	NOUN
fcis-6362	348	16	:	:	PUNCT
fcis-6362	348	17	a	a	DET
fcis-6362	348	18	case	case	NOUN
fcis-6362	348	19	study	study	NOUN
fcis-6362	348	20	of	of	ADP
fcis-6362	348	21	the	the	DET
fcis-6362	348	22	huggingface	huggingface	NOUN
fcis-6362	348	23	and	and	CCONJ
fcis-6362	348	24	gem	gem	NOUN
fcis-6362	348	25	data	datum	NOUN
fcis-6362	348	26	and	and	CCONJ
fcis-6362	348	27	model	model	NOUN
fcis-6362	348	28	cards	card	NOUN
fcis-6362	348	29	.	.	PUNCT
fcis-6362	349	1	arxiv	arxiv	PROPN
fcis-6362	349	2	preprint	preprint	NOUN
fcis-6362	349	3	arxiv:2108.07374	arxiv:2108.07374	NOUN
fcis-6362	349	4	.	.	PUNCT