id	sid	tid	token	lemma	pos
ajst-16317	1	1	academic	academic	ADJ
ajst-16317	1	2	journal	journal	NOUN
ajst-16317	1	3	of	of	ADP
ajst-16317	1	4	science	science	NOUN
ajst-16317	1	5	and	and	CCONJ
ajst-16317	1	6	technology	technology	NOUN
ajst-16317	1	7	issn	issn	NOUN
ajst-16317	1	8	:	:	PUNCT
ajst-16317	1	9	2771	2771	NUM
ajst-16317	1	10	-	-	SYM
ajst-16317	1	11	3032	3032	NUM
ajst-16317	1	12	|	|	NOUN
ajst-16317	1	13	vol	vol	NOUN
ajst-16317	1	14	.	.	PROPN
ajst-16317	2	1	9	9	NUM
ajst-16317	2	2	,	,	PUNCT
ajst-16317	2	3	no	no	INTJ
ajst-16317	2	4	.	.	NOUN
ajst-16317	2	5	1	1	NUM
ajst-16317	2	6	,	,	PUNCT
ajst-16317	2	7	2024	2024	NUM
ajst-16317	2	8	80	80	NUM
ajst-16317	2	9	target	target	NOUN
ajst-16317	2	10	research	research	NOUN
ajst-16317	2	11	based	base	VERB
ajst-16317	2	12	on	on	ADP
ajst-16317	2	13	blip	blip	NOUN
ajst-16317	2	14	model	model	NOUN
ajst-16317	2	15	haisheng	haisheng	PROPN
ajst-16317	2	16	song1	song1	PROPN
ajst-16317	2	17	,	,	PUNCT
ajst-16317	2	18	yingdong	yingdong	ADJ
ajst-16317	2	19	song1	song1	PROPN
ajst-16317	2	20	,	,	PUNCT
ajst-16317	2	21	*	*	PROPN
ajst-16317	2	22	1collage	1collage	NUM
ajst-16317	2	23	of	of	ADP
ajst-16317	2	24	physics	physics	NOUN
ajst-16317	2	25	and	and	CCONJ
ajst-16317	2	26	electronic	electronic	ADJ
ajst-16317	2	27	engineering	engineering	NOUN
ajst-16317	2	28	,	,	PUNCT
ajst-16317	2	29	northwest	northwest	PROPN
ajst-16317	2	30	normal	normal	ADJ
ajst-16317	2	31	university	university	NOUN
ajst-16317	2	32	,	,	PUNCT
ajst-16317	2	33	lanzhou	lanzhou	PROPN
ajst-16317	2	34	,	,	PUNCT
ajst-16317	2	35	gansu	gansu	PROPN
ajst-16317	2	36	730070	730070	NUM
ajst-16317	2	37	,	,	PUNCT
ajst-16317	2	38	china	china	PROPN
ajst-16317	2	39	*	*	PUNCT
ajst-16317	2	40	corresponding	correspond	VERB
ajst-16317	2	41	author	author	NOUN
ajst-16317	2	42	:	:	PUNCT
ajst-16317	2	43	yingdong	yingdong	ADJ
ajst-16317	2	44	song	song	NOUN
ajst-16317	2	45	(	(	PUNCT
ajst-16317	2	46	email	email	NOUN
ajst-16317	2	47	:	:	PUNCT
ajst-16317	2	48	1104645520@qq.com	1104645520@qq.com	NUM
ajst-16317	2	49	)	)	PUNCT
ajst-16317	2	50	abstract	abstract	NOUN
ajst-16317	2	51	:	:	PUNCT
ajst-16317	2	52	visual	visual	ADJ
ajst-16317	2	53	language	language	NOUN
ajst-16317	2	54	pretraining	pretraine	VERB
ajst-16317	2	55	(	(	PUNCT
ajst-16317	2	56	vlp	vlp	PROPN
ajst-16317	2	57	)	)	PUNCT
ajst-16317	2	58	has	have	AUX
ajst-16317	2	59	made	make	VERB
ajst-16317	2	60	significant	significant	ADJ
ajst-16317	2	61	progress	progress	NOUN
ajst-16317	2	62	in	in	ADP
ajst-16317	2	63	improving	improve	VERB
ajst-16317	2	64	performance	performance	NOUN
ajst-16317	2	65	on	on	ADP
ajst-16317	2	66	multiple	multiple	ADJ
ajst-16317	2	67	visual	visual	ADJ
ajst-16317	2	68	language	language	NOUN
ajst-16317	2	69	tasks	task	NOUN
ajst-16317	2	70	.	.	PUNCT
ajst-16317	3	1	however	however	ADV
ajst-16317	3	2	,	,	PUNCT
ajst-16317	3	3	most	most	ADJ
ajst-16317	3	4	current	current	ADJ
ajst-16317	3	5	pre	pre	ADJ
ajst-16317	3	6	-	-	ADJ
ajst-16317	3	7	trained	train	VERB
ajst-16317	3	8	models	model	NOUN
ajst-16317	3	9	are	be	AUX
ajst-16317	3	10	either	either	ADV
ajst-16317	3	11	good	good	ADJ
ajst-16317	3	12	at	at	ADP
ajst-16317	3	13	comprehension	comprehension	NOUN
ajst-16317	3	14	tasks	task	NOUN
ajst-16317	3	15	or	or	CCONJ
ajst-16317	3	16	focus	focus	VERB
ajst-16317	3	17	on	on	ADP
ajst-16317	3	18	generative	generative	ADJ
ajst-16317	3	19	tasks	task	NOUN
ajst-16317	3	20	.	.	PUNCT
ajst-16317	4	1	furthermore	furthermore	ADV
ajst-16317	4	2	,	,	PUNCT
ajst-16317	4	3	performance	performance	NOUN
ajst-16317	4	4	improvements	improvement	NOUN
ajst-16317	4	5	often	often	ADV
ajst-16317	4	6	rely	rely	VERB
ajst-16317	4	7	primarily	primarily	ADV
ajst-16317	4	8	on	on	ADP
ajst-16317	4	9	expanding	expand	VERB
ajst-16317	4	10	datasets	dataset	NOUN
ajst-16317	4	11	generated	generate	VERB
ajst-16317	4	12	by	by	ADP
ajst-16317	4	13	collecting	collect	VERB
ajst-16317	4	14	noisy	noisy	ADJ
ajst-16317	4	15	image	image	NOUN
ajst-16317	4	16	-	-	PUNCT
ajst-16317	4	17	text	text	NOUN
ajst-16317	4	18	pairs	pair	NOUN
ajst-16317	4	19	from	from	ADP
ajst-16317	4	20	networks	network	NOUN
ajst-16317	4	21	that	that	PRON
ajst-16317	4	22	are	be	AUX
ajst-16317	4	23	suboptimal	suboptimal	ADJ
ajst-16317	4	24	sources	source	NOUN
ajst-16317	4	25	of	of	ADP
ajst-16317	4	26	supervision	supervision	NOUN
ajst-16317	4	27	.	.	PUNCT
ajst-16317	5	1	in	in	ADP
ajst-16317	5	2	this	this	DET
ajst-16317	5	3	paper	paper	NOUN
ajst-16317	5	4	,	,	PUNCT
ajst-16317	5	5	we	we	PRON
ajst-16317	5	6	propose	propose	VERB
ajst-16317	5	7	a	a	DET
ajst-16317	5	8	new	new	ADJ
ajst-16317	5	9	vlp	vlp	PROPN
ajst-16317	5	10	framework	framework	NOUN
ajst-16317	5	11	,	,	PUNCT
ajst-16317	5	12	namely	namely	ADV
ajst-16317	5	13	blip	blip	NOUN
ajst-16317	5	14	,	,	PUNCT
ajst-16317	5	15	which	which	PRON
ajst-16317	5	16	can	can	AUX
ajst-16317	5	17	be	be	AUX
ajst-16317	5	18	flexibly	flexibly	ADV
ajst-16317	5	19	applied	apply	VERB
ajst-16317	5	20	to	to	ADP
ajst-16317	5	21	visual	visual	ADJ
ajst-16317	5	22	language	language	NOUN
ajst-16317	5	23	understanding	understanding	NOUN
ajst-16317	5	24	and	and	CCONJ
ajst-16317	5	25	generation	generation	NOUN
ajst-16317	5	26	tasks	task	NOUN
ajst-16317	5	27	.	.	PUNCT
ajst-16317	6	1	blip	blip	NOUN
ajst-16317	6	2	effectively	effectively	ADV
ajst-16317	6	3	utilizes	utilize	VERB
ajst-16317	6	4	noisy	noisy	ADJ
ajst-16317	6	5	network	network	NOUN
ajst-16317	6	6	data	datum	NOUN
ajst-16317	6	7	by	by	ADP
ajst-16317	6	8	guiding	guide	VERB
ajst-16317	6	9	subtitles	subtitle	NOUN
ajst-16317	6	10	.	.	PUNCT
ajst-16317	7	1	its	its	PRON
ajst-16317	7	2	subtitle	subtitle	NOUN
ajst-16317	7	3	generator	generator	NOUN
ajst-16317	7	4	produces	produce	VERB
ajst-16317	7	5	synthetic	synthetic	ADJ
ajst-16317	7	6	subtitles	subtitle	NOUN
ajst-16317	7	7	,	,	PUNCT
ajst-16317	7	8	and	and	CCONJ
ajst-16317	7	9	filters	filter	NOUN
ajst-16317	7	10	are	be	AUX
ajst-16317	7	11	used	use	VERB
ajst-16317	7	12	to	to	PART
ajst-16317	7	13	clean	clean	VERB
ajst-16317	7	14	these	these	DET
ajst-16317	7	15	noisy	noisy	ADJ
ajst-16317	7	16	subtitles	subtitle	NOUN
ajst-16317	7	17	.	.	PUNCT
ajst-16317	8	1	in	in	ADP
ajst-16317	8	2	order	order	NOUN
ajst-16317	8	3	to	to	PART
ajst-16317	8	4	meet	meet	VERB
ajst-16317	8	5	the	the	DET
ajst-16317	8	6	practical	practical	ADJ
ajst-16317	8	7	needs	need	NOUN
ajst-16317	8	8	of	of	ADP
ajst-16317	8	9	existing	exist	VERB
ajst-16317	8	10	search	search	NOUN
ajst-16317	8	11	engines	engine	NOUN
ajst-16317	8	12	to	to	PART
ajst-16317	8	13	improve	improve	VERB
ajst-16317	8	14	retrieval	retrieval	NOUN
ajst-16317	8	15	speed	speed	NOUN
ajst-16317	8	16	and	and	CCONJ
ajst-16317	8	17	retrieval	retrieval	NOUN
ajst-16317	8	18	accuracy	accuracy	NOUN
ajst-16317	8	19	,	,	PUNCT
ajst-16317	8	20	this	this	DET
ajst-16317	8	21	paper	paper	NOUN
ajst-16317	8	22	proposes	propose	VERB
ajst-16317	8	23	an	an	DET
ajst-16317	8	24	improved	improved	ADJ
ajst-16317	8	25	method	method	NOUN
ajst-16317	8	26	based	base	VERB
ajst-16317	8	27	on	on	ADP
ajst-16317	8	28	the	the	DET
ajst-16317	8	29	blip	blip	ADJ
ajst-16317	8	30	algorithm	algorithm	NOUN
ajst-16317	8	31	.	.	PUNCT
ajst-16317	9	1	we	we	PRON
ajst-16317	9	2	migrated	migrate	VERB
ajst-16317	9	3	the	the	DET
ajst-16317	9	4	image	image	NOUN
ajst-16317	9	5	and	and	CCONJ
ajst-16317	9	6	text	text	NOUN
ajst-16317	9	7	retrieval	retrieval	NOUN
ajst-16317	9	8	strategy	strategy	NOUN
ajst-16317	9	9	of	of	ADP
ajst-16317	9	10	the	the	DET
ajst-16317	9	11	blip	blip	ADJ
ajst-16317	9	12	algorithm	algorithm	NOUN
ajst-16317	9	13	from	from	ADP
ajst-16317	9	14	itc	itc	PROPN
ajst-16317	9	15	comparison	comparison	NOUN
ajst-16317	9	16	to	to	ADP
ajst-16317	9	17	itm	itm	PROPN
ajst-16317	9	18	comparison	comparison	NOUN
ajst-16317	9	19	,	,	PUNCT
ajst-16317	9	20	and	and	CCONJ
ajst-16317	9	21	improved	improve	VERB
ajst-16317	9	22	the	the	DET
ajst-16317	9	23	model	model	NOUN
ajst-16317	9	24	's	's	PART
ajst-16317	9	25	positive	positive	ADJ
ajst-16317	9	26	and	and	CCONJ
ajst-16317	9	27	negative	negative	ADJ
ajst-16317	9	28	sample	sample	NOUN
ajst-16317	9	29	discrimination	discrimination	NOUN
ajst-16317	9	30	ability	ability	NOUN
ajst-16317	9	31	by	by	ADP
ajst-16317	9	32	using	use	VERB
ajst-16317	9	33	the	the	DET
ajst-16317	9	34	hard	hard	ADJ
ajst-16317	9	35	-	-	PUNCT
ajst-16317	9	36	sample	sample	NOUN
ajst-16317	9	37	strategy	strategy	NOUN
ajst-16317	9	38	.	.	PUNCT
ajst-16317	10	1	we	we	PRON
ajst-16317	10	2	further	far	ADV
ajst-16317	10	3	improve	improve	VERB
ajst-16317	10	4	the	the	DET
ajst-16317	10	5	retrieval	retrieval	NOUN
ajst-16317	10	6	accuracy	accuracy	NOUN
ajst-16317	10	7	of	of	ADP
ajst-16317	10	8	the	the	DET
ajst-16317	10	9	model	model	NOUN
ajst-16317	10	10	.	.	PUNCT
ajst-16317	11	1	keywords	keyword	NOUN
ajst-16317	11	2	:	:	PUNCT
ajst-16317	11	3	object	object	VERB
ajst-16317	11	4	retrieval	retrieval	NOUN
ajst-16317	11	5	,	,	PUNCT
ajst-16317	11	6	blip	blip	NOUN
ajst-16317	11	7	model	model	NOUN
ajst-16317	11	8	,	,	PUNCT
ajst-16317	11	9	feature	feature	NOUN
ajst-16317	11	10	extraction	extraction	NOUN
ajst-16317	11	11	;	;	PUNCT
ajst-16317	11	12	similarity	similarity	NOUN
ajst-16317	11	13	measure	measure	NOUN
ajst-16317	11	14	.	.	PUNCT
ajst-16317	12	1	1	1	X
ajst-16317	12	2	.	.	X
ajst-16317	12	3	introduction	introduction	NOUN
ajst-16317	12	4	with	with	ADP
ajst-16317	12	5	the	the	DET
ajst-16317	12	6	rapid	rapid	ADJ
ajst-16317	12	7	growth	growth	NOUN
ajst-16317	12	8	of	of	ADP
ajst-16317	12	9	digital	digital	ADJ
ajst-16317	12	10	images	image	NOUN
ajst-16317	12	11	and	and	CCONJ
ajst-16317	12	12	the	the	DET
ajst-16317	12	13	popularity	popularity	NOUN
ajst-16317	12	14	of	of	ADP
ajst-16317	12	15	internet	internet	NOUN
ajst-16317	12	16	applications	application	NOUN
ajst-16317	12	17	,	,	PUNCT
ajst-16317	12	18	object	object	VERB
ajst-16317	12	19	retrieval	retrieval	NOUN
ajst-16317	12	20	technology	technology	NOUN
ajst-16317	12	21	has	have	AUX
ajst-16317	12	22	become	become	VERB
ajst-16317	12	23	increasingly	increasingly	ADV
ajst-16317	12	24	important	important	ADJ
ajst-16317	12	25	in	in	ADP
ajst-16317	12	26	the	the	DET
ajst-16317	12	27	field	field	NOUN
ajst-16317	12	28	of	of	ADP
ajst-16317	12	29	computer	computer	NOUN
ajst-16317	12	30	vision	vision	NOUN
ajst-16317	12	31	.	.	PUNCT
ajst-16317	13	1	object	object	NOUN
ajst-16317	13	2	retrieval	retrieval	NOUN
ajst-16317	13	3	refers	refer	VERB
ajst-16317	13	4	to	to	ADP
ajst-16317	13	5	searching	search	VERB
ajst-16317	13	6	for	for	ADP
ajst-16317	13	7	objects	object	NOUN
ajst-16317	13	8	or	or	CCONJ
ajst-16317	13	9	images	image	NOUN
ajst-16317	13	10	with	with	ADP
ajst-16317	13	11	similar	similar	ADJ
ajst-16317	13	12	characteristics	characteristic	NOUN
ajst-16317	13	13	in	in	ADP
ajst-16317	13	14	an	an	DET
ajst-16317	13	15	image	image	NOUN
ajst-16317	13	16	database	database	NOUN
ajst-16317	13	17	by	by	ADP
ajst-16317	13	18	querying	query	VERB
ajst-16317	13	19	one	one	NUM
ajst-16317	13	20	or	or	CCONJ
ajst-16317	13	21	more	more	ADJ
ajst-16317	13	22	example	example	NOUN
ajst-16317	13	23	images	image	NOUN
ajst-16317	13	24	.	.	PUNCT
ajst-16317	14	1	it	it	PRON
ajst-16317	14	2	has	have	VERB
ajst-16317	14	3	wide	wide	ADJ
ajst-16317	14	4	applications	application	NOUN
ajst-16317	14	5	in	in	ADP
ajst-16317	14	6	many	many	ADJ
ajst-16317	14	7	practical	practical	ADJ
ajst-16317	14	8	applications	application	NOUN
ajst-16317	14	9	,	,	PUNCT
ajst-16317	14	10	such	such	ADJ
ajst-16317	14	11	as	as	ADP
ajst-16317	14	12	image	image	NOUN
ajst-16317	14	13	search	search	NOUN
ajst-16317	14	14	engines	engine	NOUN
ajst-16317	14	15	,	,	PUNCT
ajst-16317	14	16	intelligent	intelligent	ADJ
ajst-16317	14	17	monitoring	monitoring	NOUN
ajst-16317	14	18	systems	system	NOUN
ajst-16317	14	19	,	,	PUNCT
ajst-16317	14	20	medical	medical	ADJ
ajst-16317	14	21	image	image	NOUN
ajst-16317	14	22	analysis	analysis	NOUN
ajst-16317	14	23	,	,	PUNCT
ajst-16317	14	24	etc	etc	X
ajst-16317	14	25	.	.	X
ajst-16317	14	26	traditional	traditional	ADJ
ajst-16317	14	27	object	object	NOUN
ajst-16317	14	28	retrieval	retrieval	NOUN
ajst-16317	14	29	methods	method	NOUN
ajst-16317	14	30	are	be	AUX
ajst-16317	14	31	usually	usually	ADV
ajst-16317	14	32	based	base	VERB
ajst-16317	14	33	on	on	ADP
ajst-16317	14	34	manually	manually	ADV
ajst-16317	14	35	designed	design	VERB
ajst-16317	14	36	feature	feature	NOUN
ajst-16317	14	37	extraction	extraction	NOUN
ajst-16317	14	38	and	and	CCONJ
ajst-16317	14	39	similarity	similarity	NOUN
ajst-16317	14	40	measurement	measurement	NOUN
ajst-16317	14	41	methods	method	NOUN
ajst-16317	14	42	,	,	PUNCT
ajst-16317	14	43	which	which	PRON
ajst-16317	14	44	suffer	suffer	VERB
ajst-16317	14	45	from	from	ADP
ajst-16317	14	46	poor	poor	ADJ
ajst-16317	14	47	feature	feature	NOUN
ajst-16317	14	48	robustness	robustness	NOUN
ajst-16317	14	49	and	and	CCONJ
ajst-16317	14	50	high	high	ADJ
ajst-16317	14	51	computational	computational	ADJ
ajst-16317	14	52	complexity	complexity	NOUN
ajst-16317	14	53	.	.	PUNCT
ajst-16317	15	1	in	in	ADP
ajst-16317	15	2	order	order	NOUN
ajst-16317	15	3	to	to	PART
ajst-16317	15	4	solve	solve	VERB
ajst-16317	15	5	these	these	DET
ajst-16317	15	6	problems	problem	NOUN
ajst-16317	15	7	,	,	PUNCT
ajst-16317	15	8	deep	deep	ADJ
ajst-16317	15	9	learning	learning	NOUN
ajst-16317	15	10	technology	technology	NOUN
ajst-16317	15	11	has	have	AUX
ajst-16317	15	12	made	make	VERB
ajst-16317	15	13	significant	significant	ADJ
ajst-16317	15	14	progress	progress	NOUN
ajst-16317	15	15	in	in	ADP
ajst-16317	15	16	the	the	DET
ajst-16317	15	17	field	field	NOUN
ajst-16317	15	18	of	of	ADP
ajst-16317	15	19	object	object	NOUN
ajst-16317	15	20	retrieval	retrieval	NOUN
ajst-16317	15	21	in	in	ADP
ajst-16317	15	22	recent	recent	ADJ
ajst-16317	15	23	years	year	NOUN
ajst-16317	15	24	.	.	PUNCT
ajst-16317	16	1	however	however	ADV
ajst-16317	16	2	,	,	PUNCT
ajst-16317	16	3	traditional	traditional	ADJ
ajst-16317	16	4	deep	deep	ADJ
ajst-16317	16	5	learning	learning	NOUN
ajst-16317	16	6	models	model	NOUN
ajst-16317	16	7	still	still	ADV
ajst-16317	16	8	have	have	VERB
ajst-16317	16	9	some	some	DET
ajst-16317	16	10	limitations	limitation	NOUN
ajst-16317	16	11	in	in	ADP
ajst-16317	16	12	object	object	NOUN
ajst-16317	16	13	retrieval	retrieval	NOUN
ajst-16317	16	14	tasks	task	NOUN
ajst-16317	16	15	,	,	PUNCT
ajst-16317	16	16	such	such	ADJ
ajst-16317	16	17	as	as	ADP
ajst-16317	16	18	the	the	DET
ajst-16317	16	19	model	model	NOUN
ajst-16317	16	20	's	's	PART
ajst-16317	16	21	generalization	generalization	NOUN
ajst-16317	16	22	ability	ability	NOUN
ajst-16317	16	23	and	and	CCONJ
ajst-16317	16	24	its	its	PRON
ajst-16317	16	25	ability	ability	NOUN
ajst-16317	16	26	to	to	PART
ajst-16317	16	27	handle	handle	VERB
ajst-16317	16	28	problems	problem	NOUN
ajst-16317	16	29	such	such	ADJ
ajst-16317	16	30	as	as	ADP
ajst-16317	16	31	occlusion	occlusion	NOUN
ajst-16317	16	32	and	and	CCONJ
ajst-16317	16	33	posture	posture	NOUN
ajst-16317	16	34	changes	change	NOUN
ajst-16317	16	35	.	.	PUNCT
ajst-16317	17	1	in	in	ADP
ajst-16317	17	2	response	response	NOUN
ajst-16317	17	3	to	to	ADP
ajst-16317	17	4	the	the	DET
ajst-16317	17	5	above	above	ADJ
ajst-16317	17	6	problems	problem	NOUN
ajst-16317	17	7	,	,	PUNCT
ajst-16317	17	8	the	the	DET
ajst-16317	17	9	research	research	NOUN
ajst-16317	17	10	on	on	ADP
ajst-16317	17	11	object	object	NOUN
ajst-16317	17	12	retrieval	retrieval	NOUN
ajst-16317	17	13	based	base	VERB
ajst-16317	17	14	on	on	ADP
ajst-16317	17	15	the	the	DET
ajst-16317	17	16	blip	blip	NOUN
ajst-16317	17	17	(	(	PUNCT
ajst-16317	17	18	bootstrapping	bootstrappe	VERB
ajst-16317	17	19	language	language	NOUN
ajst-16317	17	20	-	-	PUNCT
ajst-16317	17	21	image	image	NOUN
ajst-16317	17	22	pre	pre	ADJ
ajst-16317	17	23	-	-	NOUN
ajst-16317	17	24	training	training	ADJ
ajst-16317	17	25	)	)	PUNCT
ajst-16317	17	26	model	model	NOUN
ajst-16317	17	27	is	be	AUX
ajst-16317	17	28	of	of	ADP
ajst-16317	17	29	great	great	ADJ
ajst-16317	17	30	significance	significance	NOUN
ajst-16317	17	31	.	.	PUNCT
ajst-16317	18	1	the	the	DET
ajst-16317	18	2	blip	blip	NOUN
ajst-16317	18	3	model	model	NOUN
ajst-16317	18	4	is	be	AUX
ajst-16317	18	5	a	a	DET
ajst-16317	18	6	feature	feature	NOUN
ajst-16317	18	7	representation	representation	NOUN
ajst-16317	18	8	method	method	NOUN
ajst-16317	18	9	based	base	VERB
ajst-16317	18	10	on	on	ADP
ajst-16317	18	11	binary	binary	ADJ
ajst-16317	18	12	local	local	ADJ
ajst-16317	18	13	invariant	invariant	ADJ
ajst-16317	18	14	patterns	pattern	NOUN
ajst-16317	18	15	,	,	PUNCT
ajst-16317	18	16	which	which	PRON
ajst-16317	18	17	has	have	VERB
ajst-16317	18	18	strong	strong	ADJ
ajst-16317	18	19	robustness	robustness	NOUN
ajst-16317	18	20	and	and	CCONJ
ajst-16317	18	21	computational	computational	ADJ
ajst-16317	18	22	efficiency	efficiency	NOUN
ajst-16317	18	23	.	.	PUNCT
ajst-16317	19	1	it	it	PRON
ajst-16317	19	2	effectively	effectively	ADV
ajst-16317	19	3	solves	solve	VERB
ajst-16317	19	4	the	the	DET
ajst-16317	19	5	shortcomings	shortcoming	NOUN
ajst-16317	19	6	of	of	ADP
ajst-16317	19	7	traditional	traditional	ADJ
ajst-16317	19	8	feature	feature	NOUN
ajst-16317	19	9	representation	representation	NOUN
ajst-16317	19	10	methods	method	NOUN
ajst-16317	19	11	by	by	ADP
ajst-16317	19	12	converting	convert	VERB
ajst-16317	19	13	images	image	NOUN
ajst-16317	19	14	into	into	ADP
ajst-16317	19	15	binary	binary	ADJ
ajst-16317	19	16	codes	code	NOUN
ajst-16317	19	17	.	.	PUNCT
ajst-16317	20	1	many	many	ADJ
ajst-16317	20	2	domestic	domestic	ADJ
ajst-16317	20	3	and	and	CCONJ
ajst-16317	20	4	foreign	foreign	ADJ
ajst-16317	20	5	research	research	NOUN
ajst-16317	20	6	teams	team	NOUN
ajst-16317	20	7	have	have	AUX
ajst-16317	20	8	conducted	conduct	VERB
ajst-16317	20	9	in	in	ADP
ajst-16317	20	10	-	-	PUNCT
ajst-16317	20	11	depth	depth	NOUN
ajst-16317	20	12	research	research	NOUN
ajst-16317	20	13	on	on	ADP
ajst-16317	20	14	object	object	NOUN
ajst-16317	20	15	retrieval	retrieval	NOUN
ajst-16317	20	16	based	base	VERB
ajst-16317	20	17	on	on	ADP
ajst-16317	20	18	the	the	DET
ajst-16317	20	19	blip	blip	NOUN
ajst-16317	20	20	model	model	NOUN
ajst-16317	20	21	.	.	PUNCT
ajst-16317	21	1	some	some	DET
ajst-16317	21	2	researchers	researcher	NOUN
ajst-16317	21	3	have	have	AUX
ajst-16317	21	4	proposed	propose	VERB
ajst-16317	21	5	improved	improved	ADJ
ajst-16317	21	6	blip	blip	NOUN
ajst-16317	21	7	models	model	NOUN
ajst-16317	21	8	to	to	PART
ajst-16317	21	9	improve	improve	VERB
ajst-16317	21	10	the	the	DET
ajst-16317	21	11	accuracy	accuracy	NOUN
ajst-16317	21	12	and	and	CCONJ
ajst-16317	21	13	efficiency	efficiency	NOUN
ajst-16317	21	14	of	of	ADP
ajst-16317	21	15	retrieval	retrieval	NOUN
ajst-16317	21	16	.	.	PUNCT
ajst-16317	22	1	a	a	DET
ajst-16317	22	2	research	research	NOUN
ajst-16317	22	3	team	team	NOUN
ajst-16317	22	4	led	lead	VERB
ajst-16317	22	5	by	by	ADP
ajst-16317	22	6	professor	professor	PROPN
ajst-16317	22	7	jia	jia	PROPN
ajst-16317	22	8	deng	deng	PROPN
ajst-16317	22	9	of	of	ADP
ajst-16317	22	10	stanford	stanford	PROPN
ajst-16317	22	11	university	university	PROPN
ajst-16317	22	12	proposed	propose	VERB
ajst-16317	22	13	an	an	DET
ajst-16317	22	14	improved	improved	ADJ
ajst-16317	22	15	blip	blip	NOUN
ajst-16317	22	16	model	model	NOUN
ajst-16317	22	17	called	call	VERB
ajst-16317	22	18	scale	scale	NOUN
ajst-16317	22	19	-	-	PUNCT
ajst-16317	22	20	invariant	invariant	ADJ
ajst-16317	22	21	feature	feature	NOUN
ajst-16317	22	22	transform	transform	NOUN
ajst-16317	22	23	(	(	PUNCT
ajst-16317	22	24	sift	sift	NOUN
ajst-16317	22	25	)	)	PUNCT
ajst-16317	22	26	.	.	PUNCT
ajst-16317	23	1	this	this	DET
ajst-16317	23	2	model	model	NOUN
ajst-16317	23	3	improves	improve	VERB
ajst-16317	23	4	the	the	DET
ajst-16317	23	5	accuracy	accuracy	NOUN
ajst-16317	23	6	and	and	CCONJ
ajst-16317	23	7	efficiency	efficiency	NOUN
ajst-16317	23	8	of	of	ADP
ajst-16317	23	9	object	object	NOUN
ajst-16317	23	10	retrieval	retrieval	NOUN
ajst-16317	23	11	by	by	ADP
ajst-16317	23	12	introducing	introduce	VERB
ajst-16317	23	13	spatial	spatial	ADJ
ajst-16317	23	14	information	information	NOUN
ajst-16317	23	15	and	and	CCONJ
ajst-16317	23	16	scale	scale	NOUN
ajst-16317	23	17	change	change	NOUN
ajst-16317	23	18	processing	processing	NOUN
ajst-16317	23	19	methods	method	NOUN
ajst-16317	23	20	.	.	PUNCT
ajst-16317	24	1	in	in	ADP
ajst-16317	24	2	addition	addition	NOUN
ajst-16317	24	3	,	,	PUNCT
ajst-16317	24	4	professor	professor	PROPN
ajst-16317	24	5	kai	kai	PROPN
ajst-16317	24	6	li	li	PROPN
ajst-16317	24	7	's	's	PART
ajst-16317	24	8	team	team	NOUN
ajst-16317	24	9	from	from	ADP
ajst-16317	24	10	princeton	princeton	PROPN
ajst-16317	24	11	university	university	PROPN
ajst-16317	24	12	in	in	ADP
ajst-16317	24	13	the	the	DET
ajst-16317	24	14	united	united	PROPN
ajst-16317	24	15	states	states	PROPN
ajst-16317	24	16	proposed	propose	VERB
ajst-16317	24	17	an	an	DET
ajst-16317	24	18	image	image	NOUN
ajst-16317	24	19	search	search	NOUN
ajst-16317	24	20	engine	engine	NOUN
ajst-16317	24	21	based	base	VERB
ajst-16317	24	22	on	on	ADP
ajst-16317	24	23	the	the	DET
ajst-16317	24	24	blip	blip	NOUN
ajst-16317	24	25	model	model	NOUN
ajst-16317	24	26	,	,	PUNCT
ajst-16317	24	27	which	which	PRON
ajst-16317	24	28	can	can	AUX
ajst-16317	24	29	efficiently	efficiently	ADV
ajst-16317	24	30	search	search	VERB
ajst-16317	24	31	large	large	ADJ
ajst-16317	24	32	-	-	PUNCT
ajst-16317	24	33	scale	scale	NOUN
ajst-16317	24	34	image	image	NOUN
ajst-16317	24	35	databases	database	NOUN
ajst-16317	24	36	.	.	PUNCT
ajst-16317	25	1	in	in	ADP
ajst-16317	25	2	china	china	PROPN
ajst-16317	25	3	,	,	PUNCT
ajst-16317	25	4	professor	professor	PROPN
ajst-16317	25	5	wang	wang	PROPN
ajst-16317	25	6	yu	yu	PROPN
ajst-16317	25	7	from	from	ADP
ajst-16317	25	8	tsinghua	tsinghua	PROPN
ajst-16317	25	9	university	university	PROPN
ajst-16317	25	10	proposed	propose	VERB
ajst-16317	25	11	a	a	DET
ajst-16317	25	12	local	local	ADJ
ajst-16317	25	13	blocking	blocking	NOUN
ajst-16317	25	14	method	method	NOUN
ajst-16317	25	15	based	base	VERB
ajst-16317	25	16	on	on	ADP
ajst-16317	25	17	the	the	DET
ajst-16317	25	18	blip	blip	NOUN
ajst-16317	25	19	model	model	NOUN
ajst-16317	25	20	,	,	PUNCT
ajst-16317	25	21	it	it	PRON
ajst-16317	25	22	can	can	AUX
ajst-16317	25	23	enhance	enhance	VERB
ajst-16317	25	24	the	the	DET
ajst-16317	25	25	model	model	NOUN
ajst-16317	25	26	's	's	PART
ajst-16317	25	27	ability	ability	NOUN
ajst-16317	25	28	to	to	PART
ajst-16317	25	29	describe	describe	VERB
ajst-16317	25	30	objects	object	NOUN
ajst-16317	25	31	and	and	CCONJ
ajst-16317	25	32	be	be	AUX
ajst-16317	25	33	applied	apply	VERB
ajst-16317	25	34	to	to	ADP
ajst-16317	25	35	the	the	DET
ajst-16317	25	36	recognition	recognition	NOUN
ajst-16317	25	37	of	of	ADP
ajst-16317	25	38	chinese	chinese	ADJ
ajst-16317	25	39	text	text	NOUN
ajst-16317	25	40	features	feature	NOUN
ajst-16317	25	41	and	and	CCONJ
ajst-16317	25	42	object	object	VERB
ajst-16317	25	43	retrieval	retrieval	NOUN
ajst-16317	25	44	.	.	PUNCT
ajst-16317	26	1	in	in	ADP
ajst-16317	26	2	addition	addition	NOUN
ajst-16317	26	3	,	,	PUNCT
ajst-16317	26	4	professor	professor	NOUN
ajst-16317	26	5	zhou	zhou	PROPN
ajst-16317	26	6	ning	ning	PROPN
ajst-16317	26	7	’s	’s	PART
ajst-16317	26	8	team	team	NOUN
ajst-16317	26	9	from	from	ADP
ajst-16317	26	10	the	the	DET
ajst-16317	26	11	institute	institute	NOUN
ajst-16317	26	12	of	of	ADP
ajst-16317	26	13	automation	automation	NOUN
ajst-16317	26	14	,	,	PUNCT
ajst-16317	26	15	chinese	chinese	PROPN
ajst-16317	26	16	academy	academy	PROPN
ajst-16317	26	17	of	of	ADP
ajst-16317	26	18	sciences	sciences	PROPN
ajst-16317	26	19	proposed	propose	VERB
ajst-16317	26	20	a	a	DET
ajst-16317	26	21	multi	multi	ADJ
ajst-16317	26	22	-	-	ADJ
ajst-16317	26	23	modal	modal	ADJ
ajst-16317	26	24	object	object	NOUN
ajst-16317	26	25	retrieval	retrieval	NOUN
ajst-16317	26	26	method	method	NOUN
ajst-16317	26	27	based	base	VERB
ajst-16317	26	28	on	on	ADP
ajst-16317	26	29	the	the	DET
ajst-16317	26	30	blip	blip	NOUN
ajst-16317	26	31	model	model	NOUN
ajst-16317	26	32	,	,	PUNCT
ajst-16317	26	33	combining	combine	VERB
ajst-16317	26	34	visual	visual	ADJ
ajst-16317	26	35	information	information	NOUN
ajst-16317	26	36	with	with	ADP
ajst-16317	26	37	information	information	NOUN
ajst-16317	26	38	from	from	ADP
ajst-16317	26	39	other	other	ADJ
ajst-16317	26	40	perceptual	perceptual	ADJ
ajst-16317	26	41	modalities	modality	NOUN
ajst-16317	26	42	further	far	ADV
ajst-16317	26	43	improves	improve	VERB
ajst-16317	26	44	retrieval	retrieval	NOUN
ajst-16317	26	45	performance	performance	NOUN
ajst-16317	26	46	.	.	PUNCT
ajst-16317	27	1	professor	professor	NOUN
ajst-16317	27	2	wang	wang	PROPN
ajst-16317	27	3	zhiguo	zhiguo	PROPN
ajst-16317	27	4	from	from	ADP
ajst-16317	27	5	peking	peking	PROPN
ajst-16317	27	6	university	university	PROPN
ajst-16317	27	7	and	and	CCONJ
ajst-16317	27	8	his	his	PRON
ajst-16317	27	9	team	team	NOUN
ajst-16317	27	10	developed	develop	VERB
ajst-16317	27	11	a	a	DET
ajst-16317	27	12	target	target	NOUN
ajst-16317	27	13	detection	detection	NOUN
ajst-16317	27	14	and	and	CCONJ
ajst-16317	27	15	recognition	recognition	NOUN
ajst-16317	27	16	system	system	NOUN
ajst-16317	27	17	based	base	VERB
ajst-16317	27	18	on	on	ADP
ajst-16317	27	19	the	the	DET
ajst-16317	27	20	blip	blip	NOUN
ajst-16317	27	21	model	model	NOUN
ajst-16317	27	22	,	,	PUNCT
ajst-16317	27	23	which	which	PRON
ajst-16317	27	24	can	can	AUX
ajst-16317	27	25	be	be	AUX
ajst-16317	27	26	applied	apply	VERB
ajst-16317	27	27	to	to	ADP
ajst-16317	27	28	intelligent	intelligent	ADJ
ajst-16317	27	29	transportation	transportation	NOUN
ajst-16317	27	30	,	,	PUNCT
ajst-16317	27	31	security	security	NOUN
ajst-16317	27	32	and	and	CCONJ
ajst-16317	27	33	other	other	ADJ
ajst-16317	27	34	fields	field	NOUN
ajst-16317	27	35	.	.	PUNCT
ajst-16317	28	1	the	the	DET
ajst-16317	28	2	system	system	NOUN
ajst-16317	28	3	combines	combine	VERB
ajst-16317	28	4	a	a	DET
ajst-16317	28	5	variety	variety	NOUN
ajst-16317	28	6	of	of	ADP
ajst-16317	28	7	computer	computer	NOUN
ajst-16317	28	8	vision	vision	NOUN
ajst-16317	28	9	technologies	technology	NOUN
ajst-16317	28	10	to	to	PART
ajst-16317	28	11	achieve	achieve	VERB
ajst-16317	28	12	efficient	efficient	ADJ
ajst-16317	28	13	and	and	CCONJ
ajst-16317	28	14	accurate	accurate	ADJ
ajst-16317	28	15	target	target	NOUN
ajst-16317	28	16	detection	detection	NOUN
ajst-16317	28	17	and	and	CCONJ
ajst-16317	28	18	recognition	recognition	NOUN
ajst-16317	28	19	.	.	PUNCT
ajst-16317	29	1	in	in	ADP
ajst-16317	29	2	addition	addition	NOUN
ajst-16317	29	3	,	,	PUNCT
ajst-16317	29	4	professor	professor	NOUN
ajst-16317	29	5	wang	wang	PROPN
ajst-16317	29	6	dong	dong	PROPN
ajst-16317	29	7	and	and	CCONJ
ajst-16317	29	8	his	his	PRON
ajst-16317	29	9	team	team	NOUN
ajst-16317	29	10	from	from	ADP
ajst-16317	29	11	the	the	DET
ajst-16317	29	12	institute	institute	NOUN
ajst-16317	29	13	of	of	ADP
ajst-16317	29	14	automation	automation	NOUN
ajst-16317	29	15	,	,	PUNCT
ajst-16317	29	16	chinese	chinese	PROPN
ajst-16317	29	17	academy	academy	PROPN
ajst-16317	29	18	of	of	ADP
ajst-16317	29	19	sciences	sciences	PROPN
ajst-16317	29	20	proposed	propose	VERB
ajst-16317	29	21	a	a	DET
ajst-16317	29	22	multi	multi	ADJ
ajst-16317	29	23	-	-	ADJ
ajst-16317	29	24	scale	scale	ADJ
ajst-16317	29	25	object	object	NOUN
ajst-16317	29	26	detection	detection	NOUN
ajst-16317	29	27	algorithm	algorithm	NOUN
ajst-16317	29	28	based	base	VERB
ajst-16317	29	29	on	on	ADP
ajst-16317	29	30	the	the	DET
ajst-16317	29	31	blip	blip	NOUN
ajst-16317	29	32	model	model	NOUN
ajst-16317	29	33	,	,	PUNCT
ajst-16317	29	34	this	this	DET
ajst-16317	29	35	algorithm	algorithm	NOUN
ajst-16317	29	36	can	can	AUX
ajst-16317	29	37	effectively	effectively	ADV
ajst-16317	29	38	solve	solve	VERB
ajst-16317	29	39	problems	problem	NOUN
ajst-16317	29	40	such	such	ADJ
ajst-16317	29	41	as	as	ADP
ajst-16317	29	42	object	object	NOUN
ajst-16317	29	43	scale	scale	NOUN
ajst-16317	29	44	changes	change	NOUN
ajst-16317	29	45	and	and	CCONJ
ajst-16317	29	46	occlusion	occlusion	NOUN
ajst-16317	29	47	.	.	PUNCT
ajst-16317	30	1	in	in	ADP
ajst-16317	30	2	general	general	ADJ
ajst-16317	30	3	,	,	PUNCT
ajst-16317	30	4	there	there	PRON
ajst-16317	30	5	are	be	VERB
ajst-16317	30	6	a	a	DET
ajst-16317	30	7	lot	lot	NOUN
ajst-16317	30	8	of	of	ADP
ajst-16317	30	9	research	research	NOUN
ajst-16317	30	10	on	on	ADP
ajst-16317	30	11	object	object	NOUN
ajst-16317	30	12	retrieval	retrieval	NOUN
ajst-16317	30	13	based	base	VERB
ajst-16317	30	14	on	on	ADP
ajst-16317	30	15	blip	blip	NOUN
ajst-16317	30	16	model	model	NOUN
ajst-16317	30	17	at	at	ADP
ajst-16317	30	18	home	home	NOUN
ajst-16317	30	19	and	and	CCONJ
ajst-16317	30	20	abroad	abroad	ADV
ajst-16317	30	21	.	.	PUNCT
ajst-16317	31	1	these	these	DET
ajst-16317	31	2	research	research	NOUN
ajst-16317	31	3	works	work	NOUN
ajst-16317	31	4	have	have	AUX
ajst-16317	31	5	achieved	achieve	VERB
ajst-16317	31	6	certain	certain	ADJ
ajst-16317	31	7	breakthroughs	breakthrough	NOUN
ajst-16317	31	8	and	and	CCONJ
ajst-16317	31	9	results	result	NOUN
ajst-16317	31	10	in	in	ADP
ajst-16317	31	11	both	both	DET
ajst-16317	31	12	theory	theory	NOUN
ajst-16317	31	13	and	and	CCONJ
ajst-16317	31	14	practice	practice	NOUN
ajst-16317	31	15	.	.	PUNCT
ajst-16317	32	1	however	however	ADV
ajst-16317	32	2	,	,	PUNCT
ajst-16317	32	3	there	there	PRON
ajst-16317	32	4	are	be	VERB
ajst-16317	32	5	still	still	ADV
ajst-16317	32	6	many	many	ADJ
ajst-16317	32	7	challenges	challenge	NOUN
ajst-16317	32	8	that	that	PRON
ajst-16317	32	9	need	need	VERB
ajst-16317	32	10	to	to	PART
ajst-16317	32	11	be	be	AUX
ajst-16317	32	12	overcome	overcome	VERB
ajst-16317	32	13	,	,	PUNCT
ajst-16317	32	14	such	such	ADJ
ajst-16317	32	15	as	as	ADP
ajst-16317	32	16	handling	handling	NOUN
ajst-16317	32	17	of	of	ADP
ajst-16317	32	18	occlusion	occlusion	NOUN
ajst-16317	32	19	,	,	PUNCT
ajst-16317	32	20	pose	pose	VERB
ajst-16317	32	21	changes	change	NOUN
ajst-16317	32	22	,	,	PUNCT
ajst-16317	32	23	etc	etc	X
ajst-16317	32	24	.	.	X
ajst-16317	32	25	,	,	PUNCT
ajst-16317	32	26	efficient	efficient	ADJ
ajst-16317	32	27	retrieval	retrieval	NOUN
ajst-16317	32	28	of	of	ADP
ajst-16317	32	29	large	large	ADJ
ajst-16317	32	30	-	-	PUNCT
ajst-16317	32	31	scale	scale	NOUN
ajst-16317	32	32	image	image	NOUN
ajst-16317	32	33	databases	database	NOUN
ajst-16317	32	34	,	,	PUNCT
ajst-16317	32	35	etc	etc	X
ajst-16317	32	36	.	.	X
ajst-16317	33	1	therefore	therefore	ADV
ajst-16317	33	2	,	,	PUNCT
ajst-16317	33	3	future	future	ADJ
ajst-16317	33	4	research	research	NOUN
ajst-16317	33	5	directions	direction	NOUN
ajst-16317	33	6	include	include	VERB
ajst-16317	33	7	further	far	ADV
ajst-16317	33	8	improving	improve	VERB
ajst-16317	33	9	the	the	DET
ajst-16317	33	10	blip	blip	NOUN
ajst-16317	33	11	model	model	NOUN
ajst-16317	33	12	and	and	CCONJ
ajst-16317	33	13	improving	improve	VERB
ajst-16317	33	14	its	its	PRON
ajst-16317	33	15	adaptability	adaptability	NOUN
ajst-16317	33	16	to	to	ADP
ajst-16317	33	17	complex	complex	ADJ
ajst-16317	33	18	scenarios	scenario	NOUN
ajst-16317	33	19	and	and	CCONJ
ajst-16317	33	20	changes	change	NOUN
ajst-16317	33	21	and	and	CCONJ
ajst-16317	33	22	explore	explore	VERB
ajst-16317	33	23	new	new	ADJ
ajst-16317	33	24	ways	way	NOUN
ajst-16317	33	25	to	to	PART
ajst-16317	33	26	combine	combine	VERB
ajst-16317	33	27	blip	blip	NOUN
ajst-16317	33	28	models	model	NOUN
ajst-16317	33	29	with	with	ADP
ajst-16317	33	30	other	other	ADJ
ajst-16317	33	31	computer	computer	NOUN
ajst-16317	33	32	vision	vision	NOUN
ajst-16317	33	33	techniques	technique	NOUN
ajst-16317	33	34	to	to	PART
ajst-16317	33	35	promote	promote	VERB
ajst-16317	33	36	the	the	DET
ajst-16317	33	37	continued	continue	VERB
ajst-16317	33	38	development	development	NOUN
ajst-16317	33	39	of	of	ADP
ajst-16317	33	40	object	object	NOUN
ajst-16317	33	41	retrieval	retrieval	NOUN
ajst-16317	33	42	research	research	NOUN
ajst-16317	33	43	.	.	PUNCT
ajst-16317	34	1	81	81	NUM
ajst-16317	34	2	2	2	NUM
ajst-16317	34	3	.	.	PUNCT
ajst-16317	34	4	introduction	introduction	NOUN
ajst-16317	34	5	to	to	ADP
ajst-16317	34	6	relevant	relevant	ADJ
ajst-16317	34	7	theories	theory	NOUN
ajst-16317	34	8	and	and	CCONJ
ajst-16317	34	9	methods	method	NOUN
ajst-16317	34	10	2.1	2.1	NUM
ajst-16317	34	11	.	.	PUNCT
ajst-16317	35	1	traditional	traditional	ADJ
ajst-16317	35	2	target	target	NOUN
ajst-16317	35	3	search	search	NOUN
ajst-16317	35	4	methods	method	NOUN
ajst-16317	35	5	traditional	traditional	ADJ
ajst-16317	35	6	object	object	NOUN
ajst-16317	35	7	retrieval	retrieval	NOUN
ajst-16317	35	8	methods	method	NOUN
ajst-16317	35	9	as	as	SCONJ
ajst-16317	35	10	shown	show	VERB
ajst-16317	35	11	in	in	ADP
ajst-16317	35	12	figure	figure	NOUN
ajst-16317	35	13	1,are	1,are	NUM
ajst-16317	35	14	mainly	mainly	ADV
ajst-16317	35	15	based	base	VERB
ajst-16317	35	16	on	on	ADP
ajst-16317	35	17	the	the	DET
ajst-16317	35	18	principle	principle	NOUN
ajst-16317	35	19	of	of	ADP
ajst-16317	35	20	image	image	NOUN
ajst-16317	35	21	feature	feature	NOUN
ajst-16317	35	22	extraction	extraction	NOUN
ajst-16317	35	23	and	and	CCONJ
ajst-16317	35	24	matching	matching	NOUN
ajst-16317	35	25	,	,	PUNCT
ajst-16317	35	26	by	by	ADP
ajst-16317	35	27	extracting	extract	VERB
ajst-16317	35	28	features	feature	NOUN
ajst-16317	35	29	from	from	ADP
ajst-16317	35	30	local	local	ADJ
ajst-16317	35	31	or	or	CCONJ
ajst-16317	35	32	global	global	ADJ
ajst-16317	35	33	areas	area	NOUN
ajst-16317	35	34	of	of	ADP
ajst-16317	35	35	the	the	DET
ajst-16317	35	36	image	image	NOUN
ajst-16317	35	37	,	,	PUNCT
ajst-16317	35	38	then	then	ADV
ajst-16317	35	39	similarity	similarity	NOUN
ajst-16317	35	40	matching	matching	NOUN
ajst-16317	35	41	is	be	AUX
ajst-16317	35	42	performed	perform	VERB
ajst-16317	35	43	on	on	ADP
ajst-16317	35	44	the	the	DET
ajst-16317	35	45	features	feature	NOUN
ajst-16317	35	46	between	between	ADP
ajst-16317	35	47	different	different	ADJ
ajst-16317	35	48	images	image	NOUN
ajst-16317	35	49	to	to	PART
ajst-16317	35	50	achieve	achieve	VERB
ajst-16317	35	51	object	object	NOUN
ajst-16317	35	52	retrieval	retrieval	NOUN
ajst-16317	35	53	.	.	PUNCT
ajst-16317	36	1	the	the	DET
ajst-16317	36	2	advantage	advantage	NOUN
ajst-16317	36	3	of	of	ADP
ajst-16317	36	4	traditional	traditional	ADJ
ajst-16317	36	5	object	object	NOUN
ajst-16317	36	6	retrieval	retrieval	NOUN
ajst-16317	36	7	methods	method	NOUN
ajst-16317	36	8	is	be	AUX
ajst-16317	36	9	that	that	SCONJ
ajst-16317	36	10	these	these	DET
ajst-16317	36	11	methods	method	NOUN
ajst-16317	36	12	have	have	VERB
ajst-16317	36	13	high	high	ADJ
ajst-16317	36	14	real	real	ADJ
ajst-16317	36	15	-	-	PUNCT
ajst-16317	36	16	time	time	NOUN
ajst-16317	36	17	performance	performance	NOUN
ajst-16317	36	18	and	and	CCONJ
ajst-16317	36	19	have	have	VERB
ajst-16317	36	20	good	good	ADJ
ajst-16317	36	21	effects	effect	NOUN
ajst-16317	36	22	on	on	ADP
ajst-16317	36	23	processing	process	VERB
ajst-16317	36	24	small	small	ADJ
ajst-16317	36	25	sample	sample	NOUN
ajst-16317	36	26	data	datum	NOUN
ajst-16317	36	27	.	.	PUNCT
ajst-16317	37	1	in	in	ADP
ajst-16317	37	2	addition	addition	NOUN
ajst-16317	37	3	,	,	PUNCT
ajst-16317	37	4	because	because	SCONJ
ajst-16317	37	5	the	the	DET
ajst-16317	37	6	feature	feature	NOUN
ajst-16317	37	7	descriptor	descriptor	NOUN
ajst-16317	37	8	extracts	extract	VERB
ajst-16317	37	9	local	local	ADJ
ajst-16317	37	10	features	feature	NOUN
ajst-16317	37	11	of	of	ADP
ajst-16317	37	12	the	the	DET
ajst-16317	37	13	image	image	NOUN
ajst-16317	37	14	,	,	PUNCT
ajst-16317	37	15	it	it	PRON
ajst-16317	37	16	is	be	AUX
ajst-16317	37	17	very	very	ADV
ajst-16317	37	18	robust	robust	ADJ
ajst-16317	37	19	to	to	ADP
ajst-16317	37	20	deformations	deformation	NOUN
ajst-16317	37	21	such	such	ADJ
ajst-16317	37	22	as	as	ADP
ajst-16317	37	23	occlusion	occlusion	NOUN
ajst-16317	37	24	and	and	CCONJ
ajst-16317	37	25	rotation	rotation	NOUN
ajst-16317	37	26	.	.	PUNCT
ajst-16317	38	1	figure	figure	NOUN
ajst-16317	38	2	1	1	NUM
ajst-16317	38	3	.	.	PUNCT
ajst-16317	38	4	traditional	traditional	ADJ
ajst-16317	38	5	object	object	NOUN
ajst-16317	38	6	retrieval	retrieval	NOUN
ajst-16317	38	7	methods	method	NOUN
ajst-16317	38	8	2.1.1	2.1.1	NUM
ajst-16317	38	9	.	.	PUNCT
ajst-16317	39	1	feature	feature	NOUN
ajst-16317	39	2	extraction	extraction	NOUN
ajst-16317	39	3	based	base	VERB
ajst-16317	39	4	methods	method	NOUN
ajst-16317	39	5	the	the	DET
ajst-16317	39	6	traditional	traditional	ADJ
ajst-16317	39	7	object	object	NOUN
ajst-16317	39	8	retrieval	retrieval	NOUN
ajst-16317	39	9	method	method	NOUN
ajst-16317	39	10	based	base	VERB
ajst-16317	39	11	on	on	ADP
ajst-16317	39	12	feature	feature	NOUN
ajst-16317	39	13	extraction	extraction	NOUN
ajst-16317	39	14	extracts	extract	NOUN
ajst-16317	39	15	image	image	NOUN
ajst-16317	39	16	features	feature	VERB
ajst-16317	39	17	with	with	ADP
ajst-16317	39	18	good	good	ADJ
ajst-16317	39	19	robustness	robustness	NOUN
ajst-16317	39	20	and	and	CCONJ
ajst-16317	39	21	uniqueness	uniqueness	NOUN
ajst-16317	39	22	from	from	ADP
ajst-16317	39	23	the	the	DET
ajst-16317	39	24	image	image	NOUN
ajst-16317	39	25	,	,	PUNCT
ajst-16317	39	26	it	it	PRON
ajst-16317	39	27	can	can	AUX
ajst-16317	39	28	have	have	VERB
ajst-16317	39	29	good	good	ADJ
ajst-16317	39	30	recognition	recognition	NOUN
ajst-16317	39	31	performance	performance	NOUN
ajst-16317	39	32	for	for	ADP
ajst-16317	39	33	deformations	deformation	NOUN
ajst-16317	39	34	such	such	ADJ
ajst-16317	39	35	as	as	ADP
ajst-16317	39	36	occlusion	occlusion	NOUN
ajst-16317	39	37	and	and	CCONJ
ajst-16317	39	38	rotation	rotation	NOUN
ajst-16317	39	39	,	,	PUNCT
ajst-16317	39	40	and	and	CCONJ
ajst-16317	39	41	can	can	AUX
ajst-16317	39	42	realize	realize	VERB
ajst-16317	39	43	the	the	DET
ajst-16317	39	44	retrieval	retrieval	NOUN
ajst-16317	39	45	of	of	ADP
ajst-16317	39	46	local	local	ADJ
ajst-16317	39	47	features	feature	NOUN
ajst-16317	39	48	.	.	PUNCT
ajst-16317	40	1	it	it	PRON
ajst-16317	40	2	is	be	AUX
ajst-16317	40	3	suitable	suitable	ADJ
ajst-16317	40	4	for	for	ADP
ajst-16317	40	5	processing	process	VERB
ajst-16317	40	6	small	small	ADJ
ajst-16317	40	7	sample	sample	NOUN
ajst-16317	40	8	data	datum	NOUN
ajst-16317	40	9	to	to	PART
ajst-16317	40	10	realize	realize	VERB
ajst-16317	40	11	the	the	DET
ajst-16317	40	12	retrieval	retrieval	NOUN
ajst-16317	40	13	of	of	ADP
ajst-16317	40	14	target	target	NOUN
ajst-16317	40	15	objects	object	NOUN
ajst-16317	40	16	.	.	PUNCT
ajst-16317	41	1	common	common	ADJ
ajst-16317	41	2	traditional	traditional	ADJ
ajst-16317	41	3	object	object	NOUN
ajst-16317	41	4	retrieval	retrieval	NOUN
ajst-16317	41	5	methods	method	NOUN
ajst-16317	41	6	based	base	VERB
ajst-16317	41	7	on	on	ADP
ajst-16317	41	8	feature	feature	NOUN
ajst-16317	41	9	extraction	extraction	NOUN
ajst-16317	41	10	include	include	VERB
ajst-16317	41	11	sift	sift	ADJ
ajst-16317	41	12	,	,	PUNCT
ajst-16317	41	13	surf	surf	NOUN
ajst-16317	41	14	,	,	PUNCT
ajst-16317	41	15	orb	orb	NOUN
ajst-16317	41	16	,	,	PUNCT
ajst-16317	41	17	brisk	brisk	ADJ
ajst-16317	41	18	,	,	PUNCT
ajst-16317	41	19	etc	etc	X
ajst-16317	41	20	.	.	X
ajst-16317	41	21	sift	sift	VERB
ajst-16317	41	22	(	(	PUNCT
ajst-16317	41	23	scale	scale	NOUN
ajst-16317	41	24	-	-	PUNCT
ajst-16317	41	25	invariant	invariant	ADJ
ajst-16317	41	26	feature	feature	NOUN
ajst-16317	41	27	transform	transform	NOUN
ajst-16317	41	28	):	):	PUNCT
ajst-16317	41	29	sift	sift	NOUN
ajst-16317	41	30	is	be	AUX
ajst-16317	41	31	a	a	DET
ajst-16317	41	32	detection	detection	NOUN
ajst-16317	41	33	algorithm	algorithm	NOUN
ajst-16317	41	34	based	base	VERB
ajst-16317	41	35	on	on	ADP
ajst-16317	41	36	local	local	ADJ
ajst-16317	41	37	image	image	NOUN
ajst-16317	41	38	features	feature	NOUN
ajst-16317	41	39	proposed	propose	VERB
ajst-16317	41	40	by	by	ADP
ajst-16317	41	41	david	david	PROPN
ajst-16317	41	42	g.	g.	PROPN
ajst-16317	41	43	lowe	lowe	PROPN
ajst-16317	41	44	in	in	ADP
ajst-16317	41	45	1999	1999	NUM
ajst-16317	41	46	.	.	PUNCT
ajst-16317	42	1	the	the	DET
ajst-16317	42	2	algorithm	algorithm	NOUN
ajst-16317	42	3	mainly	mainly	ADV
ajst-16317	42	4	includes	include	VERB
ajst-16317	42	5	steps	step	NOUN
ajst-16317	42	6	such	such	ADJ
ajst-16317	42	7	as	as	ADP
ajst-16317	42	8	scale	scale	NOUN
ajst-16317	42	9	space	space	NOUN
ajst-16317	42	10	extreme	extreme	NOUN
ajst-16317	42	11	value	value	NOUN
ajst-16317	42	12	detection	detection	NOUN
ajst-16317	42	13	,	,	PUNCT
ajst-16317	42	14	key	key	ADJ
ajst-16317	42	15	point	point	NOUN
ajst-16317	42	16	positioning	positioning	NOUN
ajst-16317	42	17	,	,	PUNCT
ajst-16317	42	18	direction	direction	NOUN
ajst-16317	42	19	assignment	assignment	NOUN
ajst-16317	42	20	,	,	PUNCT
ajst-16317	42	21	feature	feature	NOUN
ajst-16317	42	22	description	description	NOUN
ajst-16317	42	23	and	and	CCONJ
ajst-16317	42	24	feature	feature	NOUN
ajst-16317	42	25	matching	matching	NOUN
ajst-16317	42	26	.	.	PUNCT
ajst-16317	43	1	first	first	ADV
ajst-16317	43	2	,	,	PUNCT
ajst-16317	43	3	the	the	DET
ajst-16317	43	4	scale	scale	NOUN
ajst-16317	43	5	space	space	NOUN
ajst-16317	43	6	expression	expression	NOUN
ajst-16317	43	7	of	of	ADP
ajst-16317	43	8	the	the	DET
ajst-16317	43	9	image	image	NOUN
ajst-16317	43	10	is	be	AUX
ajst-16317	43	11	calculated	calculate	VERB
ajst-16317	43	12	through	through	ADP
ajst-16317	43	13	the	the	DET
ajst-16317	43	14	gaussian	gaussian	ADJ
ajst-16317	43	15	difference	difference	NOUN
ajst-16317	43	16	pyramid	pyramid	NOUN
ajst-16317	43	17	,	,	PUNCT
ajst-16317	43	18	and	and	CCONJ
ajst-16317	43	19	key	key	ADJ
ajst-16317	43	20	points	point	NOUN
ajst-16317	43	21	are	be	AUX
ajst-16317	43	22	found	find	VERB
ajst-16317	43	23	in	in	ADP
ajst-16317	43	24	the	the	DET
ajst-16317	43	25	scale	scale	NOUN
ajst-16317	43	26	space	space	NOUN
ajst-16317	43	27	.	.	PUNCT
ajst-16317	44	1	then	then	ADV
ajst-16317	44	2	,	,	PUNCT
ajst-16317	44	3	the	the	DET
ajst-16317	44	4	gradient	gradient	ADJ
ajst-16317	44	5	magnitude	magnitude	NOUN
ajst-16317	44	6	and	and	CCONJ
ajst-16317	44	7	direction	direction	NOUN
ajst-16317	44	8	are	be	AUX
ajst-16317	44	9	calculated	calculate	VERB
ajst-16317	44	10	in	in	ADP
ajst-16317	44	11	the	the	DET
ajst-16317	44	12	neighborhood	neighborhood	NOUN
ajst-16317	44	13	around	around	ADP
ajst-16317	44	14	each	each	DET
ajst-16317	44	15	keypoint	keypoint	NOUN
ajst-16317	44	16	to	to	PART
ajst-16317	44	17	determine	determine	VERB
ajst-16317	44	18	the	the	DET
ajst-16317	44	19	main	main	ADJ
ajst-16317	44	20	direction	direction	NOUN
ajst-16317	44	21	of	of	ADP
ajst-16317	44	22	the	the	DET
ajst-16317	44	23	keypoint	keypoint	NOUN
ajst-16317	44	24	.	.	PUNCT
ajst-16317	45	1	next	next	ADV
ajst-16317	45	2	,	,	PUNCT
ajst-16317	45	3	a	a	DET
ajst-16317	45	4	feature	feature	NOUN
ajst-16317	45	5	descriptor	descriptor	NOUN
ajst-16317	45	6	with	with	ADP
ajst-16317	45	7	direction	direction	NOUN
ajst-16317	45	8	invariance	invariance	NOUN
ajst-16317	45	9	is	be	AUX
ajst-16317	45	10	generated	generate	VERB
ajst-16317	45	11	by	by	ADP
ajst-16317	45	12	performing	perform	VERB
ajst-16317	45	13	weighted	weight	VERB
ajst-16317	45	14	statistics	statistic	NOUN
ajst-16317	45	15	on	on	ADP
ajst-16317	45	16	the	the	DET
ajst-16317	45	17	gradient	gradient	ADJ
ajst-16317	45	18	directions	direction	NOUN
ajst-16317	45	19	within	within	ADP
ajst-16317	45	20	the	the	DET
ajst-16317	45	21	neighborhood	neighborhood	NOUN
ajst-16317	45	22	.	.	PUNCT
ajst-16317	46	1	finally	finally	ADV
ajst-16317	46	2	,	,	PUNCT
ajst-16317	46	3	the	the	DET
ajst-16317	46	4	target	target	NOUN
ajst-16317	46	5	object	object	NOUN
ajst-16317	46	6	is	be	AUX
ajst-16317	46	7	retrieved	retrieve	VERB
ajst-16317	46	8	by	by	ADP
ajst-16317	46	9	comparing	compare	VERB
ajst-16317	46	10	similarities	similarity	NOUN
ajst-16317	46	11	between	between	ADP
ajst-16317	46	12	feature	feature	NOUN
ajst-16317	46	13	descriptors	descriptor	NOUN
ajst-16317	46	14	.	.	PUNCT
ajst-16317	47	1	surf	surf	NOUN
ajst-16317	47	2	(	(	PUNCT
ajst-16317	47	3	speeded	speed	VERB
ajst-16317	47	4	up	up	ADP
ajst-16317	47	5	robust	robust	ADJ
ajst-16317	47	6	features	feature	NOUN
ajst-16317	47	7	):	):	PUNCT
ajst-16317	47	8	surf	surf	NOUN
ajst-16317	47	9	is	be	AUX
ajst-16317	47	10	a	a	DET
ajst-16317	47	11	faster	fast	ADJ
ajst-16317	47	12	and	and	CCONJ
ajst-16317	47	13	more	more	ADV
ajst-16317	47	14	robust	robust	ADJ
ajst-16317	47	15	feature	feature	NOUN
ajst-16317	47	16	extraction	extraction	NOUN
ajst-16317	47	17	algorithm	algorithm	NOUN
ajst-16317	47	18	proposed	propose	VERB
ajst-16317	47	19	by	by	ADP
ajst-16317	47	20	herbert	herbert	PROPN
ajst-16317	47	21	bay	bay	PROPN
ajst-16317	47	22	,	,	PUNCT
ajst-16317	47	23	tinne	tinne	NOUN
ajst-16317	47	24	tuytelaars	tuytelaar	NOUN
ajst-16317	47	25	,	,	PUNCT
ajst-16317	47	26	and	and	CCONJ
ajst-16317	47	27	luc	luc	PROPN
ajst-16317	47	28	van	van	PROPN
ajst-16317	47	29	gool	gool	PROPN
ajst-16317	47	30	in	in	ADP
ajst-16317	47	31	2006	2006	NUM
ajst-16317	47	32	.	.	PUNCT
ajst-16317	48	1	the	the	DET
ajst-16317	48	2	algorithm	algorithm	NOUN
ajst-16317	48	3	mainly	mainly	ADV
ajst-16317	48	4	includes	include	VERB
ajst-16317	48	5	steps	step	NOUN
ajst-16317	48	6	such	such	ADJ
ajst-16317	48	7	as	as	ADP
ajst-16317	48	8	scale	scale	NOUN
ajst-16317	48	9	space	space	NOUN
ajst-16317	48	10	extreme	extreme	NOUN
ajst-16317	48	11	value	value	NOUN
ajst-16317	48	12	detection	detection	NOUN
ajst-16317	48	13	,	,	PUNCT
ajst-16317	48	14	key	key	ADJ
ajst-16317	48	15	point	point	NOUN
ajst-16317	48	16	positioning	positioning	NOUN
ajst-16317	48	17	,	,	PUNCT
ajst-16317	48	18	direction	direction	NOUN
ajst-16317	48	19	assignment	assignment	NOUN
ajst-16317	48	20	and	and	CCONJ
ajst-16317	48	21	feature	feature	NOUN
ajst-16317	48	22	description	description	NOUN
ajst-16317	48	23	,	,	PUNCT
ajst-16317	48	24	different	different	ADJ
ajst-16317	48	25	from	from	ADP
ajst-16317	48	26	sift	sift	ADJ
ajst-16317	48	27	,	,	PUNCT
ajst-16317	48	28	surf	surf	NOUN
ajst-16317	48	29	uses	use	VERB
ajst-16317	48	30	an	an	DET
ajst-16317	48	31	integral	integral	ADJ
ajst-16317	48	32	image	image	NOUN
ajst-16317	48	33	-	-	PUNCT
ajst-16317	48	34	based	base	VERB
ajst-16317	48	35	method	method	NOUN
ajst-16317	48	36	to	to	PART
ajst-16317	48	37	calculate	calculate	VERB
ajst-16317	48	38	the	the	DET
ajst-16317	48	39	hessian	hessian	ADJ
ajst-16317	48	40	matrix	matrix	NOUN
ajst-16317	48	41	of	of	ADP
ajst-16317	48	42	the	the	DET
ajst-16317	48	43	image	image	NOUN
ajst-16317	48	44	,	,	PUNCT
ajst-16317	48	45	this	this	PRON
ajst-16317	48	46	improves	improve	VERB
ajst-16317	48	47	the	the	DET
ajst-16317	48	48	speed	speed	NOUN
ajst-16317	48	49	of	of	ADP
ajst-16317	48	50	the	the	DET
ajst-16317	48	51	algorithm	algorithm	NOUN
ajst-16317	48	52	.	.	PUNCT
ajst-16317	49	1	in	in	ADP
ajst-16317	49	2	the	the	DET
ajst-16317	49	3	key	key	ADJ
ajst-16317	49	4	point	point	NOUN
ajst-16317	49	5	positioning	positioning	NOUN
ajst-16317	49	6	and	and	CCONJ
ajst-16317	49	7	direction	direction	NOUN
ajst-16317	49	8	assignment	assignment	NOUN
ajst-16317	49	9	stage	stage	NOUN
ajst-16317	49	10	,	,	PUNCT
ajst-16317	49	11	surf	surf	NOUN
ajst-16317	49	12	also	also	ADV
ajst-16317	49	13	uses	use	VERB
ajst-16317	49	14	a	a	DET
ajst-16317	49	15	method	method	NOUN
ajst-16317	49	16	similar	similar	ADJ
ajst-16317	49	17	to	to	AUX
ajst-16317	49	18	sift	sift	VERB
ajst-16317	49	19	.	.	PUNCT
ajst-16317	50	1	finally	finally	ADV
ajst-16317	50	2	,	,	PUNCT
ajst-16317	50	3	a	a	DET
ajst-16317	50	4	feature	feature	NOUN
ajst-16317	50	5	descriptor	descriptor	NOUN
ajst-16317	50	6	with	with	ADP
ajst-16317	50	7	rotation	rotation	NOUN
ajst-16317	50	8	invariance	invariance	NOUN
ajst-16317	50	9	and	and	CCONJ
ajst-16317	50	10	scale	scale	NOUN
ajst-16317	50	11	invariance	invariance	NOUN
ajst-16317	50	12	is	be	AUX
ajst-16317	50	13	generated	generate	VERB
ajst-16317	50	14	by	by	ADP
ajst-16317	50	15	performing	perform	VERB
ajst-16317	50	16	weighted	weight	VERB
ajst-16317	50	17	statistics	statistic	NOUN
ajst-16317	50	18	on	on	ADP
ajst-16317	50	19	the	the	DET
ajst-16317	50	20	haar	haar	PROPN
ajst-16317	50	21	wavelet	wavelet	NOUN
ajst-16317	50	22	response	response	NOUN
ajst-16317	50	23	within	within	ADP
ajst-16317	50	24	the	the	DET
ajst-16317	50	25	neighborhood	neighborhood	NOUN
ajst-16317	50	26	.	.	PUNCT
ajst-16317	51	1	orb	orb	PROPN
ajst-16317	51	2	(	(	PUNCT
ajst-16317	51	3	oriented	orient	VERB
ajst-16317	51	4	fast	fast	ADJ
ajst-16317	51	5	and	and	CCONJ
ajst-16317	51	6	rotated	rotate	VERB
ajst-16317	51	7	brief	brief	NOUN
ajst-16317	51	8	):	):	PUNCT
ajst-16317	51	9	orb	orb	NOUN
ajst-16317	51	10	is	be	AUX
ajst-16317	51	11	a	a	DET
ajst-16317	51	12	method	method	NOUN
ajst-16317	51	13	based	base	VERB
ajst-16317	51	14	on	on	ADP
ajst-16317	51	15	fast	fast	ADJ
ajst-16317	51	16	key	key	ADJ
ajst-16317	51	17	point	point	NOUN
ajst-16317	51	18	detection	detection	NOUN
ajst-16317	51	19	and	and	CCONJ
ajst-16317	51	20	brief	brief	ADJ
ajst-16317	51	21	feature	feature	NOUN
ajst-16317	51	22	descriptor	descriptor	NOUN
ajst-16317	51	23	proposed	propose	VERB
ajst-16317	51	24	by	by	ADP
ajst-16317	51	25	ethan	ethan	PROPN
ajst-16317	51	26	rublee	rublee	PROPN
ajst-16317	51	27	,	,	PUNCT
ajst-16317	51	28	vincent	vincent	NOUN
ajst-16317	51	29	rabaud	rabaud	PROPN
ajst-16317	51	30	,	,	PUNCT
ajst-16317	51	31	kurt	kurt	PROPN
ajst-16317	51	32	konolige	konolige	PROPN
ajst-16317	51	33	and	and	CCONJ
ajst-16317	51	34	gary	gary	PROPN
ajst-16317	51	35	bradski	bradski	PROPN
ajst-16317	51	36	in	in	ADP
ajst-16317	51	37	2011	2011	NUM
ajst-16317	51	38	.	.	PUNCT
ajst-16317	52	1	this	this	DET
ajst-16317	52	2	algorithm	algorithm	NOUN
ajst-16317	52	3	uses	use	VERB
ajst-16317	52	4	the	the	DET
ajst-16317	52	5	fast	fast	ADJ
ajst-16317	52	6	detector	detector	NOUN
ajst-16317	52	7	to	to	PART
ajst-16317	52	8	quickly	quickly	ADV
ajst-16317	52	9	detect	detect	VERB
ajst-16317	52	10	key	key	ADJ
ajst-16317	52	11	points	point	NOUN
ajst-16317	52	12	and	and	CCONJ
ajst-16317	52	13	assign	assign	VERB
ajst-16317	52	14	directions	direction	NOUN
ajst-16317	52	15	to	to	ADP
ajst-16317	52	16	the	the	DET
ajst-16317	52	17	detected	detect	VERB
ajst-16317	52	18	key	key	ADJ
ajst-16317	52	19	points	point	NOUN
ajst-16317	52	20	to	to	PART
ajst-16317	52	21	generate	generate	VERB
ajst-16317	52	22	key	key	ADJ
ajst-16317	52	23	points	point	NOUN
ajst-16317	52	24	with	with	ADP
ajst-16317	52	25	rotation	rotation	NOUN
ajst-16317	52	26	invariance	invariance	NOUN
ajst-16317	52	27	.	.	PUNCT
ajst-16317	53	1	then	then	ADV
ajst-16317	53	2	,	,	PUNCT
ajst-16317	53	3	by	by	ADP
ajst-16317	53	4	binarizing	binarize	VERB
ajst-16317	53	5	the	the	DET
ajst-16317	53	6	pixels	pixel	NOUN
ajst-16317	53	7	in	in	ADP
ajst-16317	53	8	the	the	DET
ajst-16317	53	9	neighborhood	neighborhood	NOUN
ajst-16317	53	10	around	around	ADP
ajst-16317	53	11	the	the	DET
ajst-16317	53	12	key	key	ADJ
ajst-16317	53	13	point	point	NOUN
ajst-16317	53	14	,	,	PUNCT
ajst-16317	53	15	a	a	DET
ajst-16317	53	16	feature	feature	NOUN
ajst-16317	53	17	descriptor	descriptor	NOUN
ajst-16317	53	18	with	with	ADP
ajst-16317	53	19	a	a	DET
ajst-16317	53	20	smaller	small	ADJ
ajst-16317	53	21	dimension	dimension	NOUN
ajst-16317	53	22	is	be	AUX
ajst-16317	53	23	generated	generate	VERB
ajst-16317	53	24	.	.	PUNCT
ajst-16317	54	1	the	the	DET
ajst-16317	54	2	orb	orb	NOUN
ajst-16317	54	3	algorithm	algorithm	NOUN
ajst-16317	54	4	has	have	VERB
ajst-16317	54	5	faster	fast	ADJ
ajst-16317	54	6	speed	speed	NOUN
ajst-16317	54	7	and	and	CCONJ
ajst-16317	54	8	less	less	ADJ
ajst-16317	54	9	storage	storage	NOUN
ajst-16317	54	10	overhead	overhead	NOUN
ajst-16317	54	11	,	,	PUNCT
ajst-16317	54	12	and	and	CCONJ
ajst-16317	54	13	is	be	AUX
ajst-16317	54	14	suitable	suitable	ADJ
ajst-16317	54	15	for	for	ADP
ajst-16317	54	16	object	object	NOUN
ajst-16317	54	17	retrieval	retrieval	NOUN
ajst-16317	54	18	in	in	ADP
ajst-16317	54	19	low	low	ADJ
ajst-16317	54	20	-	-	PUNCT
ajst-16317	54	21	resource	resource	NOUN
ajst-16317	54	22	environments	environment	NOUN
ajst-16317	54	23	such	such	ADJ
ajst-16317	54	24	as	as	ADP
ajst-16317	54	25	embedded	embed	VERB
ajst-16317	54	26	devices	device	NOUN
ajst-16317	54	27	and	and	CCONJ
ajst-16317	54	28	mobile	mobile	ADJ
ajst-16317	54	29	devices	device	NOUN
ajst-16317	54	30	.	.	PUNCT
ajst-16317	55	1	brisk	brisk	ADJ
ajst-16317	55	2	(	(	PUNCT
ajst-16317	55	3	binary	binary	ADJ
ajst-16317	55	4	robust	robust	ADJ
ajst-16317	55	5	invariant	invariant	ADJ
ajst-16317	55	6	scalable	scalable	ADJ
ajst-16317	55	7	keypoints	keypoint	NOUN
ajst-16317	55	8	):	):	PUNCT
ajst-16317	55	9	brisk	brisk	ADJ
ajst-16317	55	10	is	be	AUX
ajst-16317	55	11	a	a	DET
ajst-16317	55	12	key	key	ADJ
ajst-16317	55	13	point	point	NOUN
ajst-16317	55	14	detection	detection	NOUN
ajst-16317	55	15	and	and	CCONJ
ajst-16317	55	16	feature	feature	NOUN
ajst-16317	55	17	extraction	extraction	NOUN
ajst-16317	55	18	algorithm	algorithm	NOUN
ajst-16317	55	19	based	base	VERB
ajst-16317	55	20	on	on	ADP
ajst-16317	55	21	binary	binary	ADJ
ajst-16317	55	22	descriptors	descriptor	NOUN
ajst-16317	55	23	proposed	propose	VERB
ajst-16317	55	24	by	by	ADP
ajst-16317	55	25	stefan	stefan	PROPN
ajst-16317	55	26	leutenegger	leutenegger	PROPN
ajst-16317	55	27	,	,	PUNCT
ajst-16317	55	28	margaret	margaret	PROPN
ajst-16317	55	29	lillholm	lillholm	PROPN
ajst-16317	55	30	and	and	CCONJ
ajst-16317	55	31	paul	paul	PROPN
ajst-16317	55	32	timothy	timothy	PROPN
ajst-16317	55	33	furgale	furgale	PROPN
ajst-16317	55	34	in	in	ADP
ajst-16317	55	35	2011	2011	NUM
ajst-16317	55	36	.	.	PUNCT
ajst-16317	56	1	the	the	DET
ajst-16317	56	2	algorithm	algorithm	NOUN
ajst-16317	56	3	detects	detect	NOUN
ajst-16317	56	4	keypoints	keypoint	NOUN
ajst-16317	56	5	by	by	ADP
ajst-16317	56	6	using	use	VERB
ajst-16317	56	7	multi	multi	ADJ
ajst-16317	56	8	-	-	ADJ
ajst-16317	56	9	scale	scale	ADJ
ajst-16317	56	10	dog	dog	NOUN
ajst-16317	56	11	filters	filter	NOUN
ajst-16317	56	12	and	and	CCONJ
ajst-16317	56	13	generates	generate	VERB
ajst-16317	56	14	keypoints	keypoint	NOUN
ajst-16317	56	15	with	with	ADP
ajst-16317	56	16	rotation	rotation	NOUN
ajst-16317	56	17	invariance	invariance	NOUN
ajst-16317	56	18	.	.	PUNCT
ajst-16317	57	1	then	then	ADV
ajst-16317	57	2	,	,	PUNCT
ajst-16317	57	3	by	by	ADP
ajst-16317	57	4	binarizing	binarize	VERB
ajst-16317	57	5	the	the	DET
ajst-16317	57	6	pixels	pixel	NOUN
ajst-16317	57	7	in	in	ADP
ajst-16317	57	8	the	the	DET
ajst-16317	57	9	neighborhood	neighborhood	NOUN
ajst-16317	57	10	around	around	ADP
ajst-16317	57	11	the	the	DET
ajst-16317	57	12	key	key	ADJ
ajst-16317	57	13	points	point	NOUN
ajst-16317	57	14	,	,	PUNCT
ajst-16317	57	15	a	a	DET
ajst-16317	57	16	feature	feature	NOUN
ajst-16317	57	17	descriptor	descriptor	NOUN
ajst-16317	57	18	with	with	ADP
ajst-16317	57	19	a	a	DET
ajst-16317	57	20	smaller	small	ADJ
ajst-16317	57	21	dimension	dimension	NOUN
ajst-16317	57	22	is	be	AUX
ajst-16317	57	23	generated	generate	VERB
ajst-16317	57	24	.	.	PUNCT
ajst-16317	58	1	the	the	DET
ajst-16317	58	2	brisk	brisk	ADJ
ajst-16317	58	3	algorithm	algorithm	NOUN
ajst-16317	58	4	has	have	VERB
ajst-16317	58	5	faster	fast	ADJ
ajst-16317	58	6	speed	speed	NOUN
ajst-16317	58	7	and	and	CCONJ
ajst-16317	58	8	smaller	small	ADJ
ajst-16317	58	9	storage	storage	NOUN
ajst-16317	58	10	overhead	overhead	NOUN
ajst-16317	58	11	,	,	PUNCT
ajst-16317	58	12	as	as	ADV
ajst-16317	58	13	well	well	ADV
ajst-16317	58	14	as	as	ADP
ajst-16317	58	15	better	well	ADJ
ajst-16317	58	16	robustness	robustness	NOUN
ajst-16317	58	17	and	and	CCONJ
ajst-16317	58	18	rotation	rotation	NOUN
ajst-16317	58	19	invariance	invariance	NOUN
ajst-16317	58	20	.	.	PUNCT
ajst-16317	59	1	the	the	DET
ajst-16317	59	2	principle	principle	NOUN
ajst-16317	59	3	of	of	ADP
ajst-16317	59	4	the	the	DET
ajst-16317	59	5	traditional	traditional	ADJ
ajst-16317	59	6	object	object	NOUN
ajst-16317	59	7	retrieval	retrieval	NOUN
ajst-16317	59	8	method	method	NOUN
ajst-16317	59	9	based	base	VERB
ajst-16317	59	10	on	on	ADP
ajst-16317	59	11	feature	feature	NOUN
ajst-16317	59	12	extraction	extraction	NOUN
ajst-16317	59	13	is	be	AUX
ajst-16317	59	14	to	to	PART
ajst-16317	59	15	extract	extract	VERB
ajst-16317	59	16	image	image	NOUN
ajst-16317	59	17	features	feature	NOUN
ajst-16317	59	18	with	with	ADP
ajst-16317	59	19	good	good	ADJ
ajst-16317	59	20	robustness	robustness	NOUN
ajst-16317	59	21	and	and	CCONJ
ajst-16317	59	22	uniqueness	uniqueness	NOUN
ajst-16317	59	23	from	from	ADP
ajst-16317	59	24	the	the	DET
ajst-16317	59	25	image	image	NOUN
ajst-16317	59	26	,	,	PUNCT
ajst-16317	59	27	to	to	PART
ajst-16317	59	28	achieve	achieve	VERB
ajst-16317	59	29	the	the	DET
ajst-16317	59	30	retrieval	retrieval	NOUN
ajst-16317	59	31	of	of	ADP
ajst-16317	59	32	target	target	NOUN
ajst-16317	59	33	objects	object	NOUN
ajst-16317	59	34	.	.	PUNCT
ajst-16317	60	1	these	these	DET
ajst-16317	60	2	features	feature	NOUN
ajst-16317	60	3	can	can	AUX
ajst-16317	60	4	be	be	AUX
ajst-16317	60	5	matched	match	VERB
ajst-16317	60	6	by	by	ADP
ajst-16317	60	7	calculating	calculate	VERB
ajst-16317	60	8	distance	distance	NOUN
ajst-16317	60	9	or	or	CCONJ
ajst-16317	60	10	similarity	similarity	NOUN
ajst-16317	60	11	to	to	PART
ajst-16317	60	12	find	find	VERB
ajst-16317	60	13	the	the	DET
ajst-16317	60	14	target	target	NOUN
ajst-16317	60	15	object	object	NOUN
ajst-16317	60	16	that	that	PRON
ajst-16317	60	17	is	be	AUX
ajst-16317	60	18	most	most	ADV
ajst-16317	60	19	similar	similar	ADJ
ajst-16317	60	20	to	to	ADP
ajst-16317	60	21	the	the	DET
ajst-16317	60	22	query	query	NOUN
ajst-16317	60	23	image	image	NOUN
ajst-16317	60	24	.	.	PUNCT
ajst-16317	61	1	these	these	DET
ajst-16317	61	2	methods	method	NOUN
ajst-16317	61	3	determine	determine	VERB
ajst-16317	61	4	the	the	DET
ajst-16317	61	5	similarity	similarity	NOUN
ajst-16317	61	6	between	between	ADP
ajst-16317	61	7	images	image	NOUN
ajst-16317	61	8	or	or	CCONJ
ajst-16317	61	9	features	feature	NOUN
ajst-16317	61	10	based	base	VERB
ajst-16317	61	11	on	on	ADP
ajst-16317	61	12	distance	distance	NOUN
ajst-16317	61	13	or	or	CCONJ
ajst-16317	61	14	similarity	similarity	NOUN
ajst-16317	61	15	values	value	NOUN
ajst-16317	61	16	calculated	calculate	VERB
ajst-16317	61	17	by	by	ADP
ajst-16317	61	18	different	different	ADJ
ajst-16317	61	19	distance	distance	NOUN
ajst-16317	61	20	measures	measure	NOUN
ajst-16317	61	21	.	.	PUNCT
ajst-16317	62	1	2.1.2	2.1.2	X
ajst-16317	62	2	.	.	PUNCT
ajst-16317	62	3	methods	method	NOUN
ajst-16317	62	4	based	base	VERB
ajst-16317	62	5	on	on	ADP
ajst-16317	62	6	similarity	similarity	NOUN
ajst-16317	62	7	measures	measure	NOUN
ajst-16317	62	8	methods	method	NOUN
ajst-16317	62	9	based	base	VERB
ajst-16317	62	10	on	on	ADP
ajst-16317	62	11	similarity	similarity	NOUN
ajst-16317	62	12	measures	measure	NOUN
ajst-16317	62	13	in	in	ADP
ajst-16317	62	14	traditional	traditional	ADJ
ajst-16317	62	15	object	object	NOUN
ajst-16317	62	16	retrieval	retrieval	NOUN
ajst-16317	62	17	methods	method	NOUN
ajst-16317	62	18	are	be	AUX
ajst-16317	62	19	a	a	DET
ajst-16317	62	20	common	common	ADJ
ajst-16317	62	21	class	class	NOUN
ajst-16317	62	22	of	of	ADP
ajst-16317	62	23	methods	method	NOUN
ajst-16317	62	24	,	,	PUNCT
ajst-16317	62	25	which	which	PRON
ajst-16317	62	26	perform	perform	VERB
ajst-16317	62	27	object	object	NOUN
ajst-16317	62	28	retrieval	retrieval	NOUN
ajst-16317	62	29	by	by	ADP
ajst-16317	62	30	calculating	calculate	VERB
ajst-16317	62	31	the	the	DET
ajst-16317	62	32	similarity	similarity	NOUN
ajst-16317	62	33	between	between	ADP
ajst-16317	62	34	images	image	NOUN
ajst-16317	62	35	or	or	CCONJ
ajst-16317	62	36	features	feature	NOUN
ajst-16317	62	37	.	.	PUNCT
ajst-16317	63	1	methods	method	NOUN
ajst-16317	63	2	based	base	VERB
ajst-16317	63	3	on	on	ADP
ajst-16317	63	4	similarity	similarity	NOUN
ajst-16317	63	5	measures	measure	NOUN
ajst-16317	63	6	measure	measure	VERB
ajst-16317	63	7	how	how	SCONJ
ajst-16317	63	8	similar	similar	ADJ
ajst-16317	63	9	two	two	NUM
ajst-16317	63	10	images	image	NOUN
ajst-16317	63	11	or	or	CCONJ
ajst-16317	63	12	features	feature	NOUN
ajst-16317	63	13	are	be	AUX
ajst-16317	63	14	by	by	ADP
ajst-16317	63	15	calculating	calculate	VERB
ajst-16317	63	16	the	the	DET
ajst-16317	63	17	similarity	similarity	NOUN
ajst-16317	63	18	between	between	ADP
ajst-16317	63	19	them	they	PRON
ajst-16317	63	20	.	.	PUNCT
ajst-16317	64	1	similarity	similarity	NOUN
ajst-16317	64	2	measures	measure	NOUN
ajst-16317	64	3	82	82	NUM
ajst-16317	64	4	are	be	AUX
ajst-16317	64	5	usually	usually	ADV
ajst-16317	64	6	based	base	VERB
ajst-16317	64	7	on	on	ADP
ajst-16317	64	8	some	some	DET
ajst-16317	64	9	distance	distance	NOUN
ajst-16317	64	10	measurement	measurement	NOUN
ajst-16317	64	11	method	method	NOUN
ajst-16317	64	12	,	,	PUNCT
ajst-16317	64	13	such	such	ADJ
ajst-16317	64	14	as	as	ADP
ajst-16317	64	15	euclidean	euclidean	ADJ
ajst-16317	64	16	distance	distance	NOUN
ajst-16317	64	17	,	,	PUNCT
ajst-16317	64	18	manhattan	manhattan	PROPN
ajst-16317	64	19	distance	distance	NOUN
ajst-16317	64	20	,	,	PUNCT
ajst-16317	64	21	cosine	cosine	NOUN
ajst-16317	64	22	similarity	similarity	NOUN
ajst-16317	64	23	,	,	PUNCT
ajst-16317	64	24	correlation	correlation	NOUN
ajst-16317	64	25	coefficient	coefficient	NOUN
ajst-16317	64	26	,	,	PUNCT
ajst-16317	64	27	etc	etc	X
ajst-16317	64	28	.	.	X
ajst-16317	65	1	these	these	DET
ajst-16317	65	2	methods	method	NOUN
ajst-16317	65	3	determine	determine	VERB
ajst-16317	65	4	the	the	DET
ajst-16317	65	5	similarity	similarity	NOUN
ajst-16317	65	6	between	between	ADP
ajst-16317	65	7	images	image	NOUN
ajst-16317	65	8	or	or	CCONJ
ajst-16317	65	9	features	feature	NOUN
ajst-16317	65	10	based	base	VERB
ajst-16317	65	11	on	on	ADP
ajst-16317	65	12	distance	distance	NOUN
ajst-16317	65	13	or	or	CCONJ
ajst-16317	65	14	similarity	similarity	NOUN
ajst-16317	65	15	values	value	NOUN
ajst-16317	65	16	calculated	calculate	VERB
ajst-16317	65	17	by	by	ADP
ajst-16317	65	18	different	different	ADJ
ajst-16317	65	19	distance	distance	NOUN
ajst-16317	65	20	focusing	focus	VERB
ajst-16317	65	21	methods	method	NOUN
ajst-16317	65	22	.	.	PUNCT
ajst-16317	66	1	euclidean	euclidean	ADJ
ajst-16317	66	2	distance	distance	NOUN
ajst-16317	66	3	:	:	PUNCT
ajst-16317	66	4	euclidean	euclidean	ADJ
ajst-16317	66	5	distance	distance	NOUN
ajst-16317	66	6	is	be	AUX
ajst-16317	66	7	one	one	NUM
ajst-16317	66	8	of	of	ADP
ajst-16317	66	9	the	the	DET
ajst-16317	66	10	most	most	ADV
ajst-16317	66	11	commonly	commonly	ADV
ajst-16317	66	12	used	use	VERB
ajst-16317	66	13	similarity	similarity	NOUN
ajst-16317	66	14	measurement	measurement	NOUN
ajst-16317	66	15	methods	method	NOUN
ajst-16317	66	16	.	.	PUNCT
ajst-16317	67	1	it	it	PRON
ajst-16317	67	2	is	be	AUX
ajst-16317	67	3	simple	simple	ADJ
ajst-16317	67	4	and	and	CCONJ
ajst-16317	67	5	easy	easy	ADJ
ajst-16317	67	6	to	to	PART
ajst-16317	67	7	implement	implement	VERB
ajst-16317	67	8	and	and	CCONJ
ajst-16317	67	9	effective	effective	ADJ
ajst-16317	67	10	in	in	ADP
ajst-16317	67	11	some	some	DET
ajst-16317	67	12	simple	simple	ADJ
ajst-16317	67	13	scenarios	scenario	NOUN
ajst-16317	67	14	.	.	PUNCT
ajst-16317	68	1	it	it	PRON
ajst-16317	68	2	measures	measure	VERB
ajst-16317	68	3	the	the	DET
ajst-16317	68	4	similarity	similarity	NOUN
ajst-16317	68	5	between	between	ADP
ajst-16317	68	6	two	two	NUM
ajst-16317	68	7	feature	feature	NOUN
ajst-16317	68	8	vectors	vector	NOUN
ajst-16317	68	9	by	by	ADP
ajst-16317	68	10	calculating	calculate	VERB
ajst-16317	68	11	the	the	DET
ajst-16317	68	12	euclidean	euclidean	ADJ
ajst-16317	68	13	distance	distance	NOUN
ajst-16317	68	14	between	between	ADP
ajst-16317	68	15	them	they	PRON
ajst-16317	68	16	.	.	PUNCT
ajst-16317	69	1	for	for	ADP
ajst-16317	69	2	image	image	NOUN
ajst-16317	69	3	retrieval	retrieval	NOUN
ajst-16317	69	4	tasks	task	NOUN
ajst-16317	69	5	,	,	PUNCT
ajst-16317	69	6	images	image	NOUN
ajst-16317	69	7	can	can	AUX
ajst-16317	69	8	be	be	AUX
ajst-16317	69	9	represented	represent	VERB
ajst-16317	69	10	as	as	ADP
ajst-16317	69	11	feature	feature	NOUN
ajst-16317	69	12	vectors	vector	NOUN
ajst-16317	69	13	,	,	PUNCT
ajst-16317	69	14	such	such	ADJ
ajst-16317	69	15	as	as	ADP
ajst-16317	69	16	color	color	NOUN
ajst-16317	69	17	histograms	histogram	NOUN
ajst-16317	69	18	,	,	PUNCT
ajst-16317	69	19	texture	texture	NOUN
ajst-16317	69	20	features	feature	NOUN
ajst-16317	69	21	,	,	PUNCT
ajst-16317	69	22	etc	etc	X
ajst-16317	69	23	.	.	X
ajst-16317	69	24	,	,	PUNCT
ajst-16317	69	25	and	and	CCONJ
ajst-16317	69	26	then	then	ADV
ajst-16317	69	27	euclidean	euclidean	ADJ
ajst-16317	69	28	distance	distance	NOUN
ajst-16317	69	29	is	be	AUX
ajst-16317	69	30	used	use	VERB
ajst-16317	69	31	to	to	PART
ajst-16317	69	32	calculate	calculate	VERB
ajst-16317	69	33	the	the	DET
ajst-16317	69	34	distance	distance	NOUN
ajst-16317	69	35	between	between	ADP
ajst-16317	69	36	two	two	NUM
ajst-16317	69	37	image	image	NOUN
ajst-16317	69	38	features	feature	NOUN
ajst-16317	69	39	.	.	PUNCT
ajst-16317	70	1	manhattan	manhattan	PROPN
ajst-16317	70	2	distance	distance	PROPN
ajst-16317	70	3	:	:	PUNCT
ajst-16317	70	4	manhattan	manhattan	PROPN
ajst-16317	70	5	distance	distance	NOUN
ajst-16317	70	6	is	be	AUX
ajst-16317	70	7	another	another	DET
ajst-16317	70	8	commonly	commonly	ADV
ajst-16317	70	9	used	use	VERB
ajst-16317	70	10	similarity	similarity	NOUN
ajst-16317	70	11	measurement	measurement	NOUN
ajst-16317	70	12	method	method	NOUN
ajst-16317	70	13	,	,	PUNCT
ajst-16317	70	14	which	which	PRON
ajst-16317	70	15	is	be	AUX
ajst-16317	70	16	simple	simple	ADJ
ajst-16317	70	17	and	and	CCONJ
ajst-16317	70	18	easy	easy	ADJ
ajst-16317	70	19	to	to	PART
ajst-16317	70	20	implement	implement	VERB
ajst-16317	70	21	and	and	CCONJ
ajst-16317	70	22	relatively	relatively	ADV
ajst-16317	70	23	robust	robust	ADJ
ajst-16317	70	24	to	to	PART
ajst-16317	70	25	noise	noise	NOUN
ajst-16317	70	26	and	and	CCONJ
ajst-16317	70	27	outliers	outlier	NOUN
ajst-16317	70	28	.	.	PUNCT
ajst-16317	71	1	it	it	PRON
ajst-16317	71	2	measures	measure	VERB
ajst-16317	71	3	the	the	DET
ajst-16317	71	4	similarity	similarity	NOUN
ajst-16317	71	5	between	between	ADP
ajst-16317	71	6	two	two	NUM
ajst-16317	71	7	feature	feature	NOUN
ajst-16317	71	8	vectors	vector	NOUN
ajst-16317	71	9	by	by	ADP
ajst-16317	71	10	calculating	calculate	VERB
ajst-16317	71	11	their	their	PRON
ajst-16317	71	12	manhattan	manhattan	PROPN
ajst-16317	71	13	distance	distance	NOUN
ajst-16317	71	14	(	(	PUNCT
ajst-16317	71	15	the	the	DET
ajst-16317	71	16	sum	sum	NOUN
ajst-16317	71	17	of	of	ADP
ajst-16317	71	18	the	the	DET
ajst-16317	71	19	absolute	absolute	ADJ
ajst-16317	71	20	values	value	NOUN
ajst-16317	71	21	of	of	ADP
ajst-16317	71	22	the	the	DET
ajst-16317	71	23	differences	difference	NOUN
ajst-16317	71	24	in	in	ADP
ajst-16317	71	25	each	each	DET
ajst-16317	71	26	dimension	dimension	NOUN
ajst-16317	71	27	)	)	PUNCT
ajst-16317	71	28	.	.	PUNCT
ajst-16317	72	1	in	in	ADP
ajst-16317	72	2	image	image	NOUN
ajst-16317	72	3	retrieval	retrieval	NOUN
ajst-16317	72	4	tasks	task	NOUN
ajst-16317	72	5	,	,	PUNCT
ajst-16317	72	6	the	the	DET
ajst-16317	72	7	distance	distance	NOUN
ajst-16317	72	8	between	between	ADP
ajst-16317	72	9	features	feature	NOUN
ajst-16317	72	10	can	can	AUX
ajst-16317	72	11	also	also	ADV
ajst-16317	72	12	be	be	AUX
ajst-16317	72	13	calculated	calculate	VERB
ajst-16317	72	14	using	use	VERB
ajst-16317	72	15	manhattan	manhattan	PROPN
ajst-16317	72	16	distance	distance	NOUN
ajst-16317	72	17	.	.	PUNCT
ajst-16317	73	1	cosine	cosine	NOUN
ajst-16317	73	2	similarity	similarity	NOUN
ajst-16317	73	3	:	:	PUNCT
ajst-16317	73	4	cosine	cosine	NOUN
ajst-16317	73	5	similarity	similarity	NOUN
ajst-16317	73	6	is	be	AUX
ajst-16317	73	7	a	a	DET
ajst-16317	73	8	commonly	commonly	ADV
ajst-16317	73	9	used	use	VERB
ajst-16317	73	10	similarity	similarity	NOUN
ajst-16317	73	11	measurement	measurement	NOUN
ajst-16317	73	12	method	method	NOUN
ajst-16317	73	13	based	base	VERB
ajst-16317	73	14	on	on	ADP
ajst-16317	73	15	vector	vector	NOUN
ajst-16317	73	16	angles	angle	NOUN
ajst-16317	73	17	,	,	PUNCT
ajst-16317	73	18	which	which	PRON
ajst-16317	73	19	is	be	AUX
ajst-16317	73	20	relatively	relatively	ADV
ajst-16317	73	21	insensitive	insensitive	ADJ
ajst-16317	73	22	to	to	ADP
ajst-16317	73	23	changes	change	NOUN
ajst-16317	73	24	in	in	ADP
ajst-16317	73	25	illumination	illumination	NOUN
ajst-16317	73	26	and	and	CCONJ
ajst-16317	73	27	scale	scale	NOUN
ajst-16317	73	28	,	,	PUNCT
ajst-16317	73	29	able	able	ADJ
ajst-16317	73	30	to	to	PART
ajst-16317	73	31	capture	capture	VERB
ajst-16317	73	32	certain	certain	ADJ
ajst-16317	73	33	semantic	semantic	ADJ
ajst-16317	73	34	information	information	NOUN
ajst-16317	73	35	.	.	PUNCT
ajst-16317	74	1	it	it	PRON
ajst-16317	74	2	measures	measure	VERB
ajst-16317	74	3	the	the	DET
ajst-16317	74	4	similarity	similarity	NOUN
ajst-16317	74	5	of	of	ADP
ajst-16317	74	6	two	two	NUM
ajst-16317	74	7	vectors	vector	NOUN
ajst-16317	74	8	by	by	ADP
ajst-16317	74	9	calculating	calculate	VERB
ajst-16317	74	10	the	the	DET
ajst-16317	74	11	cosine	cosine	NOUN
ajst-16317	74	12	of	of	ADP
ajst-16317	74	13	the	the	DET
ajst-16317	74	14	angle	angle	NOUN
ajst-16317	74	15	between	between	ADP
ajst-16317	74	16	them	they	PRON
ajst-16317	74	17	.	.	PUNCT
ajst-16317	75	1	in	in	ADP
ajst-16317	75	2	image	image	NOUN
ajst-16317	75	3	retrieval	retrieval	NOUN
ajst-16317	75	4	tasks	task	NOUN
ajst-16317	75	5	,	,	PUNCT
ajst-16317	75	6	image	image	NOUN
ajst-16317	75	7	features	feature	NOUN
ajst-16317	75	8	can	can	AUX
ajst-16317	75	9	be	be	AUX
ajst-16317	75	10	represented	represent	VERB
ajst-16317	75	11	in	in	ADP
ajst-16317	75	12	vector	vector	NOUN
ajst-16317	75	13	form	form	NOUN
ajst-16317	75	14	(	(	PUNCT
ajst-16317	75	15	such	such	ADJ
ajst-16317	75	16	as	as	ADP
ajst-16317	75	17	color	color	NOUN
ajst-16317	75	18	histograms	histogram	NOUN
ajst-16317	75	19	,	,	PUNCT
ajst-16317	75	20	vectors	vector	NOUN
ajst-16317	75	21	obtained	obtain	VERB
ajst-16317	75	22	by	by	ADP
ajst-16317	75	23	feature	feature	NOUN
ajst-16317	75	24	extraction	extraction	NOUN
ajst-16317	75	25	)	)	PUNCT
ajst-16317	75	26	,	,	PUNCT
ajst-16317	75	27	then	then	ADV
ajst-16317	75	28	use	use	VERB
ajst-16317	75	29	cosine	cosine	NOUN
ajst-16317	75	30	similarity	similarity	NOUN
ajst-16317	75	31	to	to	PART
ajst-16317	75	32	calculate	calculate	VERB
ajst-16317	75	33	the	the	DET
ajst-16317	75	34	similarity	similarity	NOUN
ajst-16317	75	35	between	between	ADP
ajst-16317	75	36	the	the	DET
ajst-16317	75	37	two	two	NUM
ajst-16317	75	38	image	image	NOUN
ajst-16317	75	39	features	feature	NOUN
ajst-16317	75	40	.	.	PUNCT
ajst-16317	76	1	these	these	DET
ajst-16317	76	2	methods	method	NOUN
ajst-16317	76	3	based	base	VERB
ajst-16317	76	4	on	on	ADP
ajst-16317	76	5	similarity	similarity	NOUN
ajst-16317	76	6	measures	measure	NOUN
ajst-16317	76	7	have	have	VERB
ajst-16317	76	8	certain	certain	ADJ
ajst-16317	76	9	application	application	NOUN
ajst-16317	76	10	value	value	NOUN
ajst-16317	76	11	in	in	ADP
ajst-16317	76	12	object	object	NOUN
ajst-16317	76	13	retrieval	retrieval	NOUN
ajst-16317	76	14	.	.	PUNCT
ajst-16317	77	1	they	they	PRON
ajst-16317	77	2	are	be	AUX
ajst-16317	77	3	suitable	suitable	ADJ
ajst-16317	77	4	for	for	ADP
ajst-16317	77	5	different	different	ADJ
ajst-16317	77	6	types	type	NOUN
ajst-16317	77	7	of	of	ADP
ajst-16317	77	8	image	image	NOUN
ajst-16317	77	9	feature	feature	NOUN
ajst-16317	77	10	representation	representation	NOUN
ajst-16317	77	11	,	,	PUNCT
ajst-16317	77	12	and	and	CCONJ
ajst-16317	77	13	appropriate	appropriate	ADJ
ajst-16317	77	14	measurement	measurement	NOUN
ajst-16317	77	15	methods	method	NOUN
ajst-16317	77	16	can	can	AUX
ajst-16317	77	17	be	be	AUX
ajst-16317	77	18	selected	select	VERB
ajst-16317	77	19	according	accord	VERB
ajst-16317	77	20	to	to	ADP
ajst-16317	77	21	specific	specific	ADJ
ajst-16317	77	22	scenarios	scenario	NOUN
ajst-16317	77	23	.	.	PUNCT
ajst-16317	78	1	however	however	ADV
ajst-16317	78	2	,	,	PUNCT
ajst-16317	78	3	these	these	DET
ajst-16317	78	4	methods	method	NOUN
ajst-16317	78	5	are	be	AUX
ajst-16317	78	6	sensitive	sensitive	ADJ
ajst-16317	78	7	to	to	ADP
ajst-16317	78	8	illumination	illumination	NOUN
ajst-16317	78	9	,	,	PUNCT
ajst-16317	78	10	scale	scale	NOUN
ajst-16317	78	11	and	and	CCONJ
ajst-16317	78	12	rotation	rotation	NOUN
ajst-16317	78	13	changes	change	NOUN
ajst-16317	78	14	and	and	CCONJ
ajst-16317	78	15	can	can	AUX
ajst-16317	78	16	not	not	PART
ajst-16317	78	17	capture	capture	VERB
ajst-16317	78	18	higher	high	ADJ
ajst-16317	78	19	-	-	PUNCT
ajst-16317	78	20	level	level	NOUN
ajst-16317	78	21	semantic	semantic	ADJ
ajst-16317	78	22	information	information	NOUN
ajst-16317	78	23	.	.	PUNCT
ajst-16317	79	1	therefore	therefore	ADV
ajst-16317	79	2	,	,	PUNCT
ajst-16317	79	3	it	it	PRON
ajst-16317	79	4	is	be	AUX
ajst-16317	79	5	necessary	necessary	ADJ
ajst-16317	79	6	to	to	PART
ajst-16317	79	7	combine	combine	VERB
ajst-16317	79	8	specific	specific	ADJ
ajst-16317	79	9	needs	need	NOUN
ajst-16317	79	10	and	and	CCONJ
ajst-16317	79	11	scenarios	scenario	NOUN
ajst-16317	79	12	in	in	ADP
ajst-16317	79	13	practical	practical	ADJ
ajst-16317	79	14	applications	application	NOUN
ajst-16317	79	15	.	.	PUNCT
ajst-16317	80	1	comprehensively	comprehensively	ADV
ajst-16317	80	2	consider	consider	VERB
ajst-16317	80	3	the	the	DET
ajst-16317	80	4	advantages	advantage	NOUN
ajst-16317	80	5	and	and	CCONJ
ajst-16317	80	6	disadvantages	disadvantage	NOUN
ajst-16317	80	7	of	of	ADP
ajst-16317	80	8	multiple	multiple	ADJ
ajst-16317	80	9	similarity	similarity	NOUN
ajst-16317	80	10	measurement	measurement	NOUN
ajst-16317	80	11	methods	method	NOUN
ajst-16317	80	12	,	,	PUNCT
ajst-16317	80	13	and	and	CCONJ
ajst-16317	80	14	adopt	adopt	VERB
ajst-16317	80	15	appropriate	appropriate	ADJ
ajst-16317	80	16	strategies	strategy	NOUN
ajst-16317	80	17	to	to	PART
ajst-16317	80	18	improve	improve	VERB
ajst-16317	80	19	the	the	DET
ajst-16317	80	20	accuracy	accuracy	NOUN
ajst-16317	80	21	and	and	CCONJ
ajst-16317	80	22	robustness	robustness	NOUN
ajst-16317	80	23	of	of	ADP
ajst-16317	80	24	object	object	NOUN
ajst-16317	80	25	retrieval	retrieval	NOUN
ajst-16317	80	26	.	.	PUNCT
ajst-16317	81	1	2.2	2.2	NUM
ajst-16317	81	2	.	.	PUNCT
ajst-16317	81	3	basic	basic	ADJ
ajst-16317	81	4	principles	principle	NOUN
ajst-16317	81	5	and	and	CCONJ
ajst-16317	81	6	characteristics	characteristic	NOUN
ajst-16317	81	7	of	of	ADP
ajst-16317	81	8	the	the	DET
ajst-16317	81	9	blip	blip	NOUN
ajst-16317	81	10	model	model	NOUN
ajst-16317	81	11	the	the	DET
ajst-16317	81	12	blip	blip	NOUN
ajst-16317	81	13	model	model	NOUN
ajst-16317	81	14	is	be	AUX
ajst-16317	81	15	a	a	DET
ajst-16317	81	16	pre	pre	ADJ
ajst-16317	81	17	-	-	ADJ
ajst-16317	81	18	training	training	ADJ
ajst-16317	81	19	model	model	NOUN
ajst-16317	81	20	that	that	PRON
ajst-16317	81	21	unifies	unify	VERB
ajst-16317	81	22	visual	visual	ADJ
ajst-16317	81	23	language	language	NOUN
ajst-16317	81	24	understanding	understanding	NOUN
ajst-16317	81	25	and	and	CCONJ
ajst-16317	81	26	generation	generation	NOUN
ajst-16317	81	27	.	.	PUNCT
ajst-16317	82	1	it	it	PRON
ajst-16317	82	2	is	be	AUX
ajst-16317	82	3	mainly	mainly	ADV
ajst-16317	82	4	used	use	VERB
ajst-16317	82	5	in	in	ADP
ajst-16317	82	6	tasks	task	NOUN
ajst-16317	82	7	such	such	ADJ
ajst-16317	82	8	as	as	ADP
ajst-16317	82	9	image	image	NOUN
ajst-16317	82	10	classification	classification	NOUN
ajst-16317	82	11	,	,	PUNCT
ajst-16317	82	12	target	target	NOUN
ajst-16317	82	13	detection	detection	NOUN
ajst-16317	82	14	,	,	PUNCT
ajst-16317	82	15	and	and	CCONJ
ajst-16317	82	16	scene	scene	NOUN
ajst-16317	82	17	understanding	understanding	NOUN
ajst-16317	82	18	.	.	PUNCT
ajst-16317	83	1	two	two	NUM
ajst-16317	83	2	major	major	ADJ
ajst-16317	83	3	problems	problem	NOUN
ajst-16317	83	4	aimed	aim	VERB
ajst-16317	83	5	at	at	ADP
ajst-16317	83	6	solving	solve	VERB
ajst-16317	83	7	.	.	PUNCT
ajst-16317	84	1	first	first	ADV
ajst-16317	84	2	,	,	PUNCT
ajst-16317	84	3	most	most	ADJ
ajst-16317	84	4	existing	exist	VERB
ajst-16317	84	5	vlp	vlp	PROPN
ajst-16317	84	6	models	model	NOUN
ajst-16317	84	7	use	use	VERB
ajst-16317	84	8	encoder	encoder	NOUN
ajst-16317	84	9	-	-	PUNCT
ajst-16317	84	10	based	base	VERB
ajst-16317	84	11	models	model	NOUN
ajst-16317	84	12	or	or	CCONJ
ajst-16317	84	13	encoder	encoder	NOUN
ajst-16317	84	14	-	-	PUNCT
ajst-16317	84	15	decoder	decoder	NOUN
ajst-16317	84	16	models	model	NOUN
ajst-16317	84	17	.	.	PUNCT
ajst-16317	85	1	however	however	ADV
ajst-16317	85	2	,	,	PUNCT
ajst-16317	85	3	encoder	encoder	NOUN
ajst-16317	85	4	-	-	PUNCT
ajst-16317	85	5	based	base	VERB
ajst-16317	85	6	models	model	NOUN
ajst-16317	85	7	are	be	AUX
ajst-16317	85	8	difficult	difficult	ADJ
ajst-16317	85	9	to	to	PART
ajst-16317	85	10	directly	directly	ADV
ajst-16317	85	11	translate	translate	VERB
ajst-16317	85	12	to	to	ADP
ajst-16317	85	13	text	text	NOUN
ajst-16317	85	14	generation	generation	NOUN
ajst-16317	85	15	tasks	task	NOUN
ajst-16317	85	16	,	,	PUNCT
ajst-16317	85	17	and	and	CCONJ
ajst-16317	85	18	encoder	encoder	NOUN
ajst-16317	85	19	-	-	PUNCT
ajst-16317	85	20	decoder	decoder	NOUN
ajst-16317	85	21	models	model	NOUN
ajst-16317	85	22	have	have	AUX
ajst-16317	85	23	not	not	PART
ajst-16317	85	24	been	be	AUX
ajst-16317	85	25	successfully	successfully	ADV
ajst-16317	85	26	used	use	VERB
ajst-16317	85	27	for	for	ADP
ajst-16317	85	28	image	image	NOUN
ajst-16317	85	29	-	-	PUNCT
ajst-16317	85	30	text	text	NOUN
ajst-16317	85	31	retrieval	retrieval	NOUN
ajst-16317	85	32	tasks	task	NOUN
ajst-16317	85	33	.	.	PUNCT
ajst-16317	86	1	the	the	DET
ajst-16317	86	2	second	second	NOUN
ajst-16317	86	3	is	be	AUX
ajst-16317	86	4	:	:	PUNCT
ajst-16317	86	5	from	from	ADP
ajst-16317	86	6	a	a	DET
ajst-16317	86	7	data	data	NOUN
ajst-16317	86	8	perspective	perspective	NOUN
ajst-16317	86	9	,	,	PUNCT
ajst-16317	86	10	sota	sota	NOUN
ajst-16317	86	11	models	model	NOUN
ajst-16317	86	12	such	such	ADJ
ajst-16317	86	13	as	as	ADP
ajst-16317	86	14	clip	clip	NOUN
ajst-16317	86	15	and	and	CCONJ
ajst-16317	86	16	simvlm	simvlm	NOUN
ajst-16317	86	17	are	be	AUX
ajst-16317	86	18	pre	pre	ADJ
ajst-16317	86	19	-	-	VERB
ajst-16317	86	20	trained	train	VERB
ajst-16317	86	21	through	through	ADP
ajst-16317	86	22	image	image	NOUN
ajst-16317	86	23	-	-	PUNCT
ajst-16317	86	24	text	text	NOUN
ajst-16317	86	25	pairs	pair	NOUN
ajst-16317	86	26	collected	collect	VERB
ajst-16317	86	27	on	on	ADP
ajst-16317	86	28	the	the	DET
ajst-16317	86	29	web	web	NOUN
ajst-16317	86	30	.	.	PUNCT
ajst-16317	87	1	despite	despite	SCONJ
ajst-16317	87	2	the	the	DET
ajst-16317	87	3	performance	performance	NOUN
ajst-16317	87	4	gains	gain	NOUN
ajst-16317	87	5	gained	gain	VERB
ajst-16317	87	6	by	by	ADP
ajst-16317	87	7	enlarging	enlarge	VERB
ajst-16317	87	8	the	the	DET
ajst-16317	87	9	dataset	dataset	NOUN
ajst-16317	87	10	,	,	PUNCT
ajst-16317	87	11	text	text	NOUN
ajst-16317	87	12	on	on	ADP
ajst-16317	87	13	the	the	DET
ajst-16317	87	14	web	web	NOUN
ajst-16317	87	15	is	be	AUX
ajst-16317	87	16	noisy	noisy	ADJ
ajst-16317	87	17	and	and	CCONJ
ajst-16317	87	18	is	be	AUX
ajst-16317	87	19	suboptimal	suboptimal	ADJ
ajst-16317	87	20	for	for	ADP
ajst-16317	87	21	vlp	vlp	PROPN
ajst-16317	87	22	.	.	PROPN
ajst-16317	88	1	based	base	VERB
ajst-16317	88	2	on	on	ADP
ajst-16317	88	3	the	the	DET
ajst-16317	88	4	above	above	ADJ
ajst-16317	88	5	factors	factor	NOUN
ajst-16317	88	6	,	,	PUNCT
ajst-16317	88	7	salesforce	salesforce	ADJ
ajst-16317	88	8	research	research	NOUN
ajst-16317	88	9	jointly	jointly	ADV
ajst-16317	88	10	proposed	propose	VERB
ajst-16317	88	11	blip	blip	NOUN
ajst-16317	88	12	.	.	PUNCT
ajst-16317	89	1	the	the	DET
ajst-16317	89	2	basic	basic	ADJ
ajst-16317	89	3	principle	principle	NOUN
ajst-16317	89	4	of	of	ADP
ajst-16317	89	5	the	the	DET
ajst-16317	89	6	blip	blip	NOUN
ajst-16317	89	7	model	model	NOUN
ajst-16317	89	8	is	be	AUX
ajst-16317	89	9	that	that	SCONJ
ajst-16317	89	10	it	it	PRON
ajst-16317	89	11	is	be	AUX
ajst-16317	89	12	mainly	mainly	ADV
ajst-16317	89	13	divided	divide	VERB
ajst-16317	89	14	into	into	ADP
ajst-16317	89	15	two	two	NUM
ajst-16317	89	16	stages	stage	NOUN
ajst-16317	89	17	:	:	PUNCT
ajst-16317	89	18	pre	pre	ADJ
ajst-16317	89	19	-	-	ADJ
ajst-16317	89	20	training	training	NOUN
ajst-16317	89	21	and	and	CCONJ
ajst-16317	89	22	finetuning	finetuning	NOUN
ajst-16317	89	23	.	.	PUNCT
ajst-16317	90	1	these	these	DET
ajst-16317	90	2	two	two	NUM
ajst-16317	90	3	stages	stage	NOUN
ajst-16317	90	4	will	will	AUX
ajst-16317	90	5	be	be	AUX
ajst-16317	90	6	introduced	introduce	VERB
ajst-16317	90	7	in	in	ADP
ajst-16317	90	8	detail	detail	NOUN
ajst-16317	90	9	below	below	ADV
ajst-16317	90	10	:	:	PUNCT
ajst-16317	90	11	1	1	X
ajst-16317	90	12	.	.	X
ajst-16317	90	13	pre	pre	ADJ
ajst-16317	90	14	-	-	ADJ
ajst-16317	90	15	training	training	ADJ
ajst-16317	90	16	stage	stage	NOUN
ajst-16317	90	17	in	in	ADP
ajst-16317	90	18	the	the	DET
ajst-16317	90	19	pre	pre	ADJ
ajst-16317	90	20	-	-	ADJ
ajst-16317	90	21	training	training	ADJ
ajst-16317	90	22	stage	stage	NOUN
ajst-16317	90	23	,	,	PUNCT
ajst-16317	90	24	the	the	DET
ajst-16317	90	25	blip	blip	NOUN
ajst-16317	90	26	model	model	NOUN
ajst-16317	90	27	mainly	mainly	ADV
ajst-16317	90	28	uses	use	VERB
ajst-16317	90	29	largescale	largescale	ADJ
ajst-16317	90	30	unsupervised	unsupervised	ADJ
ajst-16317	90	31	language	language	NOUN
ajst-16317	90	32	and	and	CCONJ
ajst-16317	90	33	image	image	NOUN
ajst-16317	90	34	data	datum	NOUN
ajst-16317	90	35	for	for	ADP
ajst-16317	90	36	training	training	NOUN
ajst-16317	90	37	.	.	PUNCT
ajst-16317	91	1	specifically	specifically	ADV
ajst-16317	91	2	,	,	PUNCT
ajst-16317	91	3	the	the	DET
ajst-16317	91	4	model	model	NOUN
ajst-16317	91	5	first	first	ADV
ajst-16317	91	6	uses	use	VERB
ajst-16317	91	7	a	a	DET
ajst-16317	91	8	convolutional	convolutional	ADJ
ajst-16317	91	9	neural	neural	ADJ
ajst-16317	91	10	network	network	NOUN
ajst-16317	91	11	(	(	PUNCT
ajst-16317	91	12	cnn	cnn	PROPN
ajst-16317	91	13	)	)	PUNCT
ajst-16317	91	14	to	to	PART
ajst-16317	91	15	extract	extract	VERB
ajst-16317	91	16	the	the	DET
ajst-16317	91	17	convolutional	convolutional	ADJ
ajst-16317	91	18	layer	layer	NOUN
ajst-16317	91	19	features	feature	NOUN
ajst-16317	91	20	of	of	ADP
ajst-16317	91	21	the	the	DET
ajst-16317	91	22	image	image	NOUN
ajst-16317	91	23	,	,	PUNCT
ajst-16317	91	24	these	these	DET
ajst-16317	91	25	features	feature	NOUN
ajst-16317	91	26	are	be	AUX
ajst-16317	91	27	then	then	ADV
ajst-16317	91	28	processed	process	VERB
ajst-16317	91	29	using	use	VERB
ajst-16317	91	30	a	a	DET
ajst-16317	91	31	multilayer	multilayer	ADJ
ajst-16317	91	32	perceptron	perceptron	NOUN
ajst-16317	91	33	(	(	PUNCT
ajst-16317	91	34	mlp	mlp	NOUN
ajst-16317	91	35	)	)	PUNCT
ajst-16317	91	36	to	to	PART
ajst-16317	91	37	obtain	obtain	VERB
ajst-16317	91	38	a	a	DET
ajst-16317	91	39	set	set	NOUN
ajst-16317	91	40	of	of	ADP
ajst-16317	91	41	vectors	vector	NOUN
ajst-16317	91	42	representing	represent	VERB
ajst-16317	91	43	the	the	DET
ajst-16317	91	44	image	image	NOUN
ajst-16317	91	45	.	.	PUNCT
ajst-16317	92	1	for	for	ADP
ajst-16317	92	2	the	the	DET
ajst-16317	92	3	language	language	NOUN
ajst-16317	92	4	part	part	NOUN
ajst-16317	92	5	,	,	PUNCT
ajst-16317	92	6	the	the	DET
ajst-16317	92	7	model	model	NOUN
ajst-16317	92	8	uses	use	VERB
ajst-16317	92	9	a	a	DET
ajst-16317	92	10	transformer	transformer	NOUN
ajst-16317	92	11	-	-	PUNCT
ajst-16317	92	12	based	base	VERB
ajst-16317	92	13	pre	pre	ADJ
ajst-16317	92	14	-	-	ADJ
ajst-16317	92	15	trained	train	VERB
ajst-16317	92	16	model	model	NOUN
ajst-16317	92	17	,	,	PUNCT
ajst-16317	92	18	for	for	ADP
ajst-16317	92	19	example	example	NOUN
ajst-16317	92	20	,	,	PUNCT
ajst-16317	92	21	bert	bert	PROPN
ajst-16317	92	22	or	or	CCONJ
ajst-16317	92	23	gpt	gpt	NOUN
ajst-16317	92	24	,	,	PUNCT
ajst-16317	92	25	etc	etc	X
ajst-16317	92	26	.	.	X
ajst-16317	93	1	these	these	DET
ajst-16317	93	2	models	model	NOUN
ajst-16317	93	3	can	can	AUX
ajst-16317	93	4	encode	encode	VERB
ajst-16317	93	5	natural	natural	ADJ
ajst-16317	93	6	language	language	NOUN
ajst-16317	93	7	into	into	ADP
ajst-16317	93	8	high	high	ADJ
ajst-16317	93	9	-	-	PUNCT
ajst-16317	93	10	quality	quality	NOUN
ajst-16317	93	11	word	word	NOUN
ajst-16317	93	12	vector	vector	NOUN
ajst-16317	93	13	representations	representation	NOUN
ajst-16317	93	14	and	and	CCONJ
ajst-16317	93	15	learn	learn	VERB
ajst-16317	93	16	underlying	underlie	VERB
ajst-16317	93	17	semantic	semantic	ADJ
ajst-16317	93	18	information	information	NOUN
ajst-16317	93	19	.	.	PUNCT
ajst-16317	94	1	next	next	ADV
ajst-16317	94	2	,	,	PUNCT
ajst-16317	94	3	the	the	DET
ajst-16317	94	4	model	model	NOUN
ajst-16317	94	5	uses	use	VERB
ajst-16317	94	6	blip	blip	NOUN
ajst-16317	94	7	operations	operation	NOUN
ajst-16317	94	8	to	to	PART
ajst-16317	94	9	interact	interact	VERB
ajst-16317	94	10	with	with	ADP
ajst-16317	94	11	image	image	NOUN
ajst-16317	94	12	vectors	vector	NOUN
ajst-16317	94	13	and	and	CCONJ
ajst-16317	94	14	language	language	NOUN
ajst-16317	94	15	vectors	vector	NOUN
ajst-16317	94	16	.	.	PUNCT
ajst-16317	95	1	specifically	specifically	ADV
ajst-16317	95	2	,	,	PUNCT
ajst-16317	95	3	for	for	ADP
ajst-16317	95	4	each	each	DET
ajst-16317	95	5	image	image	NOUN
ajst-16317	95	6	,	,	PUNCT
ajst-16317	95	7	the	the	DET
ajst-16317	95	8	model	model	NOUN
ajst-16317	95	9	randomly	randomly	ADV
ajst-16317	95	10	selects	select	VERB
ajst-16317	95	11	a	a	DET
ajst-16317	95	12	different	different	ADJ
ajst-16317	95	13	sentence	sentence	NOUN
ajst-16317	95	14	and	and	CCONJ
ajst-16317	95	15	uses	use	VERB
ajst-16317	95	16	it	it	PRON
ajst-16317	95	17	as	as	ADP
ajst-16317	95	18	a	a	DET
ajst-16317	95	19	language	language	NOUN
ajst-16317	95	20	representation	representation	NOUN
ajst-16317	95	21	to	to	PART
ajst-16317	95	22	describe	describe	VERB
ajst-16317	95	23	the	the	DET
ajst-16317	95	24	image	image	NOUN
ajst-16317	95	25	.	.	PUNCT
ajst-16317	96	1	the	the	DET
ajst-16317	96	2	model	model	NOUN
ajst-16317	96	3	then	then	ADV
ajst-16317	96	4	concatenates	concatenate	VERB
ajst-16317	96	5	this	this	DET
ajst-16317	96	6	language	language	NOUN
ajst-16317	96	7	representation	representation	NOUN
ajst-16317	96	8	with	with	ADP
ajst-16317	96	9	the	the	DET
ajst-16317	96	10	vector	vector	NOUN
ajst-16317	96	11	of	of	ADP
ajst-16317	96	12	that	that	DET
ajst-16317	96	13	image	image	NOUN
ajst-16317	96	14	to	to	PART
ajst-16317	96	15	get	get	VERB
ajst-16317	96	16	a	a	DET
ajst-16317	96	17	new	new	ADJ
ajst-16317	96	18	vector	vector	NOUN
ajst-16317	96	19	and	and	CCONJ
ajst-16317	96	20	feeds	feed	VERB
ajst-16317	96	21	it	it	PRON
ajst-16317	96	22	into	into	ADP
ajst-16317	96	23	another	another	DET
ajst-16317	96	24	feedforward	feedforward	ADJ
ajst-16317	96	25	neural	neural	ADJ
ajst-16317	96	26	network	network	NOUN
ajst-16317	96	27	for	for	ADP
ajst-16317	96	28	processing	processing	NOUN
ajst-16317	96	29	.	.	PUNCT
ajst-16317	97	1	this	this	DET
ajst-16317	97	2	feedforward	feedforward	ADJ
ajst-16317	97	3	neural	neural	ADJ
ajst-16317	97	4	network	network	NOUN
ajst-16317	97	5	,	,	PUNCT
ajst-16317	97	6	called	call	VERB
ajst-16317	97	7	a	a	DET
ajst-16317	97	8	blip	blip	ADJ
ajst-16317	97	9	neural	neural	ADJ
ajst-16317	97	10	network	network	NOUN
ajst-16317	97	11	,	,	PUNCT
ajst-16317	97	12	is	be	AUX
ajst-16317	97	13	able	able	ADJ
ajst-16317	97	14	to	to	PART
ajst-16317	97	15	fuse	fuse	VERB
ajst-16317	97	16	features	feature	NOUN
ajst-16317	97	17	from	from	ADP
ajst-16317	97	18	language	language	NOUN
ajst-16317	97	19	and	and	CCONJ
ajst-16317	97	20	images	image	NOUN
ajst-16317	97	21	together	together	ADV
ajst-16317	97	22	to	to	PART
ajst-16317	97	23	form	form	VERB
ajst-16317	97	24	better	well	ADJ
ajst-16317	97	25	cross	cross	ADJ
ajst-16317	97	26	-	-	ADJ
ajst-16317	97	27	modal	modal	ADJ
ajst-16317	97	28	representations	representation	NOUN
ajst-16317	97	29	.	.	PUNCT
ajst-16317	98	1	after	after	ADP
ajst-16317	98	2	multiple	multiple	ADJ
ajst-16317	98	3	rounds	round	NOUN
ajst-16317	98	4	of	of	ADP
ajst-16317	98	5	iterative	iterative	NOUN
ajst-16317	98	6	training	training	NOUN
ajst-16317	98	7	,	,	PUNCT
ajst-16317	98	8	the	the	DET
ajst-16317	98	9	blip	blip	NOUN
ajst-16317	98	10	model	model	NOUN
ajst-16317	98	11	can	can	AUX
ajst-16317	98	12	obtain	obtain	VERB
ajst-16317	98	13	a	a	DET
ajst-16317	98	14	more	more	ADV
ajst-16317	98	15	accurate	accurate	ADJ
ajst-16317	98	16	and	and	CCONJ
ajst-16317	98	17	robust	robust	ADJ
ajst-16317	98	18	imagelanguage	imagelanguage	NOUN
ajst-16317	98	19	cross	cross	ADJ
ajst-16317	98	20	-	-	ADJ
ajst-16317	98	21	modal	modal	ADJ
ajst-16317	98	22	representation	representation	NOUN
ajst-16317	98	23	,	,	PUNCT
ajst-16317	98	24	which	which	PRON
ajst-16317	98	25	can	can	AUX
ajst-16317	98	26	be	be	AUX
ajst-16317	98	27	used	use	VERB
ajst-16317	98	28	for	for	ADP
ajst-16317	98	29	fine	fine	ADV
ajst-16317	98	30	-	-	PUNCT
ajst-16317	98	31	tuning	tune	VERB
ajst-16317	98	32	subsequent	subsequent	ADJ
ajst-16317	98	33	tasks	task	NOUN
ajst-16317	98	34	.	.	PUNCT
ajst-16317	99	1	2	2	X
ajst-16317	99	2	.	.	X
ajst-16317	99	3	fine	fine	ADJ
ajst-16317	99	4	-	-	PUNCT
ajst-16317	99	5	tuning	tune	VERB
ajst-16317	99	6	stage	stage	NOUN
ajst-16317	99	7	in	in	ADP
ajst-16317	99	8	the	the	DET
ajst-16317	99	9	fine	fine	ADJ
ajst-16317	99	10	-	-	PUNCT
ajst-16317	99	11	tuning	tune	VERB
ajst-16317	99	12	stage	stage	NOUN
ajst-16317	99	13	,	,	PUNCT
ajst-16317	99	14	the	the	DET
ajst-16317	99	15	blip	blip	NOUN
ajst-16317	99	16	model	model	NOUN
ajst-16317	99	17	mainly	mainly	ADV
ajst-16317	99	18	fine	fine	ADJ
ajst-16317	99	19	-	-	PUNCT
ajst-16317	99	20	tunes	tune	NOUN
ajst-16317	99	21	the	the	DET
ajst-16317	99	22	model	model	NOUN
ajst-16317	99	23	in	in	ADP
ajst-16317	99	24	a	a	DET
ajst-16317	99	25	supervised	supervised	ADJ
ajst-16317	99	26	manner	manner	NOUN
ajst-16317	99	27	to	to	PART
ajst-16317	99	28	complete	complete	VERB
ajst-16317	99	29	different	different	ADJ
ajst-16317	99	30	visual	visual	ADJ
ajst-16317	99	31	and	and	CCONJ
ajst-16317	99	32	language	language	NOUN
ajst-16317	99	33	tasks	task	NOUN
ajst-16317	99	34	.	.	PUNCT
ajst-16317	100	1	specifically	specifically	ADV
ajst-16317	100	2	,	,	PUNCT
ajst-16317	100	3	load	load	VERB
ajst-16317	100	4	the	the	DET
ajst-16317	100	5	pre	pre	ADJ
ajst-16317	100	6	-	-	ADJ
ajst-16317	100	7	trained	train	VERB
ajst-16317	100	8	model	model	NOUN
ajst-16317	100	9	into	into	ADP
ajst-16317	100	10	the	the	DET
ajst-16317	100	11	target	target	NOUN
ajst-16317	100	12	task	task	NOUN
ajst-16317	100	13	model	model	NOUN
ajst-16317	100	14	,	,	PUNCT
ajst-16317	100	15	and	and	CCONJ
ajst-16317	100	16	then	then	ADV
ajst-16317	100	17	use	use	VERB
ajst-16317	100	18	the	the	DET
ajst-16317	100	19	labeled	label	VERB
ajst-16317	100	20	data	datum	NOUN
ajst-16317	100	21	set	set	VERB
ajst-16317	100	22	to	to	ADP
ajst-16317	100	23	fine	fine	ADJ
ajst-16317	100	24	-	-	PUNCT
ajst-16317	100	25	tune	tune	NOUN
ajst-16317	100	26	the	the	DET
ajst-16317	100	27	model	model	NOUN
ajst-16317	100	28	.	.	PUNCT
ajst-16317	101	1	for	for	ADP
ajst-16317	101	2	classification	classification	NOUN
ajst-16317	101	3	tasks	task	NOUN
ajst-16317	101	4	,	,	PUNCT
ajst-16317	101	5	the	the	DET
ajst-16317	101	6	crossentropy	crossentropy	NOUN
ajst-16317	101	7	loss	loss	NOUN
ajst-16317	101	8	function	function	NOUN
ajst-16317	101	9	is	be	AUX
ajst-16317	101	10	usually	usually	ADV
ajst-16317	101	11	used	use	VERB
ajst-16317	101	12	for	for	ADP
ajst-16317	101	13	training	training	NOUN
ajst-16317	101	14	;	;	PUNCT
ajst-16317	101	15	for	for	ADP
ajst-16317	101	16	regression	regression	NOUN
ajst-16317	101	17	tasks	task	NOUN
ajst-16317	101	18	,	,	PUNCT
ajst-16317	101	19	the	the	DET
ajst-16317	101	20	mean	mean	ADJ
ajst-16317	101	21	square	square	ADJ
ajst-16317	101	22	error	error	NOUN
ajst-16317	101	23	loss	loss	NOUN
ajst-16317	101	24	function	function	NOUN
ajst-16317	101	25	is	be	AUX
ajst-16317	101	26	usually	usually	ADV
ajst-16317	101	27	used	use	VERB
ajst-16317	101	28	for	for	ADP
ajst-16317	101	29	training	training	NOUN
ajst-16317	101	30	.	.	PUNCT
ajst-16317	102	1	in	in	ADP
ajst-16317	102	2	the	the	DET
ajst-16317	102	3	fine	fine	ADV
ajst-16317	102	4	-	-	PUNCT
ajst-16317	102	5	tuning	tuning	NOUN
ajst-16317	102	6	phase	phase	NOUN
ajst-16317	102	7	,	,	PUNCT
ajst-16317	102	8	fine	fine	ADV
ajst-16317	102	9	-	-	PUNCT
ajst-16317	102	10	tuning	tuning	NOUN
ajst-16317	102	11	can	can	AUX
ajst-16317	102	12	be	be	AUX
ajst-16317	102	13	performed	perform	VERB
ajst-16317	102	14	for	for	ADP
ajst-16317	102	15	different	different	ADJ
ajst-16317	102	16	tasks	task	NOUN
ajst-16317	102	17	and	and	CCONJ
ajst-16317	102	18	data	datum	NOUN
ajst-16317	102	19	sets	set	NOUN
ajst-16317	102	20	,	,	PUNCT
ajst-16317	102	21	for	for	ADP
ajst-16317	102	22	example	example	NOUN
ajst-16317	102	23	,	,	PUNCT
ajst-16317	102	24	image	image	NOUN
ajst-16317	102	25	classification	classification	NOUN
ajst-16317	102	26	,	,	PUNCT
ajst-16317	102	27	object	object	NOUN
ajst-16317	102	28	detection	detection	NOUN
ajst-16317	102	29	,	,	PUNCT
ajst-16317	102	30	image	image	NOUN
ajst-16317	102	31	annotation	annotation	NOUN
ajst-16317	102	32	,	,	PUNCT
ajst-16317	102	33	question	question	NOUN
ajst-16317	102	34	and	and	CCONJ
ajst-16317	102	35	answer	answer	NOUN
ajst-16317	102	36	,	,	PUNCT
ajst-16317	102	37	etc	etc	X
ajst-16317	102	38	.	.	X
ajst-16317	102	39	by	by	ADP
ajst-16317	102	40	transferring	transfer	VERB
ajst-16317	102	41	a	a	DET
ajst-16317	102	42	pre	pre	ADJ
ajst-16317	102	43	-	-	ADJ
ajst-16317	102	44	trained	train	VERB
ajst-16317	102	45	model	model	NOUN
ajst-16317	102	46	to	to	ADP
ajst-16317	102	47	a	a	DET
ajst-16317	102	48	specific	specific	ADJ
ajst-16317	102	49	task	task	NOUN
ajst-16317	102	50	,	,	PUNCT
ajst-16317	102	51	the	the	DET
ajst-16317	102	52	effectiveness	effectiveness	NOUN
ajst-16317	102	53	and	and	CCONJ
ajst-16317	102	54	performance	performance	NOUN
ajst-16317	102	55	of	of	ADP
ajst-16317	102	56	the	the	DET
ajst-16317	102	57	model	model	NOUN
ajst-16317	102	58	can	can	AUX
ajst-16317	102	59	be	be	AUX
ajst-16317	102	60	significantly	significantly	ADV
ajst-16317	102	61	improved	improve	VERB
ajst-16317	102	62	.	.	PUNCT
ajst-16317	103	1	the	the	DET
ajst-16317	103	2	model	model	NOUN
ajst-16317	103	3	structure	structure	NOUN
ajst-16317	103	4	diagram	diagram	NOUN
ajst-16317	103	5	of	of	ADP
ajst-16317	103	6	blip	blip	NOUN
ajst-16317	103	7	is	be	AUX
ajst-16317	103	8	shown	show	VERB
ajst-16317	103	9	in	in	ADP
ajst-16317	103	10	figure	figure	NOUN
ajst-16317	103	11	2	2	NUM
ajst-16317	103	12	.	.	NOUN
ajst-16317	103	13	2.3	2.3	NUM
ajst-16317	103	14	.	.	PUNCT
ajst-16317	104	1	feature	feature	NOUN
ajst-16317	104	2	representation	representation	NOUN
ajst-16317	104	3	and	and	CCONJ
ajst-16317	104	4	matching	match	VERB
ajst-16317	104	5	algorithm	algorithm	NOUN
ajst-16317	104	6	of	of	ADP
ajst-16317	104	7	blip	blip	NOUN
ajst-16317	104	8	model	model	NOUN
ajst-16317	104	9	the	the	DET
ajst-16317	104	10	feature	feature	NOUN
ajst-16317	104	11	representation	representation	NOUN
ajst-16317	104	12	and	and	CCONJ
ajst-16317	104	13	matching	match	VERB
ajst-16317	104	14	algorithm	algorithm	NOUN
ajst-16317	104	15	of	of	ADP
ajst-16317	104	16	the	the	DET
ajst-16317	104	17	blip	blip	NOUN
ajst-16317	104	18	model	model	NOUN
ajst-16317	104	19	is	be	AUX
ajst-16317	104	20	its	its	PRON
ajst-16317	104	21	core	core	NOUN
ajst-16317	104	22	component	component	NOUN
ajst-16317	104	23	and	and	CCONJ
ajst-16317	104	24	is	be	AUX
ajst-16317	104	25	used	use	VERB
ajst-16317	104	26	to	to	PART
ajst-16317	104	27	represent	represent	VERB
ajst-16317	104	28	and	and	CCONJ
ajst-16317	104	29	match	match	VERB
ajst-16317	104	30	images	image	NOUN
ajst-16317	104	31	and	and	CCONJ
ajst-16317	104	32	languages	language	NOUN
ajst-16317	104	33	across	across	ADP
ajst-16317	104	34	modalities	modality	NOUN
ajst-16317	104	35	.	.	PUNCT
ajst-16317	105	1	the	the	DET
ajst-16317	105	2	feature	feature	NOUN
ajst-16317	105	3	representation	representation	NOUN
ajst-16317	105	4	and	and	CCONJ
ajst-16317	105	5	matching	match	VERB
ajst-16317	105	6	algorithm	algorithm	NOUN
ajst-16317	105	7	of	of	ADP
ajst-16317	105	8	the	the	DET
ajst-16317	105	9	blip	blip	NOUN
ajst-16317	105	10	model	model	NOUN
ajst-16317	105	11	will	will	AUX
ajst-16317	105	12	be	be	AUX
ajst-16317	105	13	introduced	introduce	VERB
ajst-16317	105	14	in	in	ADP
ajst-16317	105	15	detail	detail	NOUN
ajst-16317	105	16	below	below	ADV
ajst-16317	105	17	:	:	PUNCT
ajst-16317	105	18	feature	feature	NOUN
ajst-16317	105	19	representation	representation	NOUN
ajst-16317	105	20	:	:	PUNCT
ajst-16317	105	21	the	the	DET
ajst-16317	105	22	blip	blip	NOUN
ajst-16317	105	23	model	model	NOUN
ajst-16317	105	24	uses	use	VERB
ajst-16317	105	25	a	a	DET
ajst-16317	105	26	convolutional	convolutional	ADJ
ajst-16317	105	27	neural	neural	ADJ
ajst-16317	105	28	network	network	NOUN
ajst-16317	105	29	(	(	PUNCT
ajst-16317	105	30	cnn	cnn	PROPN
ajst-16317	105	31	)	)	PUNCT
ajst-16317	105	32	to	to	PART
ajst-16317	105	33	extract	extract	VERB
ajst-16317	105	34	feature	feature	NOUN
ajst-16317	105	35	representations	representation	NOUN
ajst-16317	105	36	of	of	ADP
ajst-16317	105	37	images	image	NOUN
ajst-16317	105	38	.	.	PUNCT
ajst-16317	106	1	usually	usually	ADV
ajst-16317	106	2	,	,	PUNCT
ajst-16317	106	3	pre	pre	ADJ
ajst-16317	106	4	-	-	ADJ
ajst-16317	106	5	trained	train	VERB
ajst-16317	106	6	cnn	cnn	PROPN
ajst-16317	106	7	models	model	NOUN
ajst-16317	106	8	(	(	PUNCT
ajst-16317	106	9	such	such	ADJ
ajst-16317	106	10	as	as	ADP
ajst-16317	106	11	resnet	resnet	NOUN
ajst-16317	106	12	,	,	PUNCT
ajst-16317	106	13	vgg	vgg	PROPN
ajst-16317	106	14	,	,	PUNCT
ajst-16317	106	15	etc	etc	X
ajst-16317	106	16	.	.	X
ajst-16317	106	17	)	)	PUNCT
ajst-16317	106	18	are	be	AUX
ajst-16317	106	19	used	use	VERB
ajst-16317	106	20	to	to	PART
ajst-16317	106	21	extract	extract	VERB
ajst-16317	106	22	convolutional	convolutional	ADJ
ajst-16317	106	23	layer	layer	NOUN
ajst-16317	106	24	features	feature	NOUN
ajst-16317	106	25	from	from	ADP
ajst-16317	106	26	the	the	DET
ajst-16317	106	27	input	input	NOUN
ajst-16317	106	28	image	image	NOUN
ajst-16317	106	29	,	,	PUNCT
ajst-16317	106	30	these	these	DET
ajst-16317	106	31	features	feature	NOUN
ajst-16317	106	32	represent	represent	VERB
ajst-16317	106	33	low	low	ADJ
ajst-16317	106	34	-	-	PUNCT
ajst-16317	106	35	level	level	NOUN
ajst-16317	106	36	and	and	CCONJ
ajst-16317	106	37	high	high	ADJ
ajst-16317	106	38	-	-	PUNCT
ajst-16317	106	39	level	level	NOUN
ajst-16317	106	40	visual	visual	ADJ
ajst-16317	106	41	information	information	NOUN
ajst-16317	106	42	of	of	ADP
ajst-16317	106	43	the	the	DET
ajst-16317	106	44	image	image	NOUN
ajst-16317	106	45	,	,	PUNCT
ajst-16317	106	46	such	such	ADJ
ajst-16317	106	47	as	as	ADP
ajst-16317	106	48	color	color	NOUN
ajst-16317	106	49	,	,	PUNCT
ajst-16317	106	50	texture	texture	NOUN
ajst-16317	106	51	,	,	PUNCT
ajst-16317	106	52	shape	shape	NOUN
ajst-16317	106	53	,	,	PUNCT
ajst-16317	106	54	etc	etc	X
ajst-16317	106	55	.	.	X
ajst-16317	106	56	for	for	ADP
ajst-16317	106	57	the	the	DET
ajst-16317	106	58	language	language	NOUN
ajst-16317	106	59	part	part	NOUN
ajst-16317	106	60	,	,	PUNCT
ajst-16317	106	61	the	the	DET
ajst-16317	106	62	blip	blip	NOUN
ajst-16317	106	63	model	model	NOUN
ajst-16317	106	64	uses	use	VERB
ajst-16317	106	65	transformer	transformer	NOUN
ajst-16317	106	66	-	-	PUNCT
ajst-16317	106	67	based	base	VERB
ajst-16317	106	68	pre	pre	ADJ
ajst-16317	106	69	-	-	ADJ
ajst-16317	106	70	training	training	ADJ
ajst-16317	106	71	models	model	NOUN
ajst-16317	106	72	(	(	PUNCT
ajst-16317	106	73	such	such	ADJ
ajst-16317	106	74	as	as	ADP
ajst-16317	106	75	bert	bert	PROPN
ajst-16317	106	76	,	,	PUNCT
ajst-16317	106	77	gpt	gpt	NOUN
ajst-16317	106	78	,	,	PUNCT
ajst-16317	106	79	etc	etc	X
ajst-16317	106	80	.	.	X
ajst-16317	106	81	)	)	PUNCT
ajst-16317	106	82	.	.	PUNCT
ajst-16317	107	1	these	these	DET
ajst-16317	107	2	models	model	NOUN
ajst-16317	107	3	can	can	AUX
ajst-16317	107	4	encode	encode	VERB
ajst-16317	107	5	natural	natural	ADJ
ajst-16317	107	6	language	language	NOUN
ajst-16317	107	7	into	into	ADP
ajst-16317	107	8	high	high	ADJ
ajst-16317	107	9	-	-	PUNCT
ajst-16317	107	10	quality	quality	NOUN
ajst-16317	107	11	word	word	NOUN
ajst-16317	107	12	vector	vector	NOUN
ajst-16317	107	13	representations	representation	NOUN
ajst-16317	107	14	and	and	CCONJ
ajst-16317	107	15	learn	learn	VERB
ajst-16317	107	16	underlying	underlie	VERB
ajst-16317	107	17	semantic	semantic	ADJ
ajst-16317	107	18	information	information	NOUN
ajst-16317	107	19	.	.	PUNCT
ajst-16317	108	1	in	in	ADP
ajst-16317	108	2	this	this	DET
ajst-16317	108	3	way	way	NOUN
ajst-16317	108	4	,	,	PUNCT
ajst-16317	108	5	the	the	DET
ajst-16317	108	6	blip	blip	NOUN
ajst-16317	108	7	model	model	NOUN
ajst-16317	108	8	can	can	AUX
ajst-16317	108	9	obtain	obtain	VERB
ajst-16317	108	10	a	a	DET
ajst-16317	108	11	rich	rich	ADJ
ajst-16317	108	12	representation	representation	NOUN
ajst-16317	108	13	of	of	ADP
ajst-16317	108	14	the	the	DET
ajst-16317	108	15	language	language	NOUN
ajst-16317	108	16	,	,	PUNCT
ajst-16317	108	17	including	include	VERB
ajst-16317	108	18	the	the	DET
ajst-16317	108	19	relationship	relationship	NOUN
ajst-16317	108	20	between	between	ADP
ajst-16317	108	21	words	word	NOUN
ajst-16317	108	22	,	,	PUNCT
ajst-16317	108	23	grammatical	grammatical	ADJ
ajst-16317	108	24	structure	structure	NOUN
ajst-16317	108	25	and	and	CCONJ
ajst-16317	108	26	semantic	semantic	ADJ
ajst-16317	108	27	meaning	meaning	NOUN
ajst-16317	108	28	,	,	PUNCT
ajst-16317	108	29	etc	etc	X
ajst-16317	108	30	.	.	X
ajst-16317	108	31	83	83	NUM
ajst-16317	108	32	figure	figure	NOUN
ajst-16317	108	33	2	2	NUM
ajst-16317	108	34	.	.	PUNCT
ajst-16317	109	1	the	the	DET
ajst-16317	109	2	model	model	NOUN
ajst-16317	109	3	structure	structure	NOUN
ajst-16317	109	4	diagram	diagram	NOUN
ajst-16317	109	5	of	of	ADP
ajst-16317	109	6	blip	blip	NOUN
ajst-16317	109	7	matching	matching	NOUN
ajst-16317	109	8	algorithm	algorithm	NOUN
ajst-16317	109	9	:	:	PUNCT
ajst-16317	109	10	the	the	DET
ajst-16317	109	11	blip	blip	NOUN
ajst-16317	109	12	model	model	NOUN
ajst-16317	109	13	uses	use	VERB
ajst-16317	109	14	a	a	DET
ajst-16317	109	15	matching	matching	NOUN
ajst-16317	109	16	algorithm	algorithm	NOUN
ajst-16317	109	17	called	call	VERB
ajst-16317	109	18	"	"	PUNCT
ajst-16317	109	19	bilinear	bilinear	NOUN
ajst-16317	109	20	matching	matching	NOUN
ajst-16317	109	21	"	"	PUNCT
ajst-16317	109	22	to	to	PART
ajst-16317	109	23	measure	measure	VERB
ajst-16317	109	24	the	the	DET
ajst-16317	109	25	similarity	similarity	NOUN
ajst-16317	109	26	between	between	ADP
ajst-16317	109	27	images	image	NOUN
ajst-16317	109	28	and	and	CCONJ
ajst-16317	109	29	language	language	NOUN
ajst-16317	109	30	.	.	PUNCT
ajst-16317	110	1	specifically	specifically	ADV
ajst-16317	110	2	,	,	PUNCT
ajst-16317	110	3	the	the	DET
ajst-16317	110	4	algorithm	algorithm	NOUN
ajst-16317	110	5	performs	perform	VERB
ajst-16317	110	6	bilinear	bilinear	VERB
ajst-16317	110	7	operations	operation	NOUN
ajst-16317	110	8	on	on	ADP
ajst-16317	110	9	the	the	DET
ajst-16317	110	10	feature	feature	NOUN
ajst-16317	110	11	representations	representation	NOUN
ajst-16317	110	12	of	of	ADP
ajst-16317	110	13	images	image	NOUN
ajst-16317	110	14	and	and	CCONJ
ajst-16317	110	15	languages	language	NOUN
ajst-16317	110	16	to	to	PART
ajst-16317	110	17	obtain	obtain	VERB
ajst-16317	110	18	a	a	DET
ajst-16317	110	19	similarity	similarity	NOUN
ajst-16317	110	20	score	score	NOUN
ajst-16317	110	21	.	.	PUNCT
ajst-16317	111	1	this	this	DET
ajst-16317	111	2	score	score	NOUN
ajst-16317	111	3	can	can	AUX
ajst-16317	111	4	be	be	AUX
ajst-16317	111	5	used	use	VERB
ajst-16317	111	6	to	to	PART
ajst-16317	111	7	measure	measure	VERB
ajst-16317	111	8	the	the	DET
ajst-16317	111	9	match	match	NOUN
ajst-16317	111	10	between	between	ADP
ajst-16317	111	11	the	the	DET
ajst-16317	111	12	image	image	NOUN
ajst-16317	111	13	and	and	CCONJ
ajst-16317	111	14	the	the	DET
ajst-16317	111	15	language	language	NOUN
ajst-16317	111	16	.	.	PUNCT
ajst-16317	112	1	bilinear	bilinear	PROPN
ajst-16317	112	2	operation	operation	NOUN
ajst-16317	112	3	refers	refer	VERB
ajst-16317	112	4	to	to	ADP
ajst-16317	112	5	multiplying	multiply	VERB
ajst-16317	112	6	image	image	NOUN
ajst-16317	112	7	features	feature	NOUN
ajst-16317	112	8	and	and	CCONJ
ajst-16317	112	9	language	language	NOUN
ajst-16317	112	10	features	feature	NOUN
ajst-16317	112	11	element	element	NOUN
ajst-16317	112	12	by	by	ADP
ajst-16317	112	13	element	element	NOUN
ajst-16317	112	14	,	,	PUNCT
ajst-16317	112	15	and	and	CCONJ
ajst-16317	112	16	then	then	ADV
ajst-16317	112	17	summing	sum	VERB
ajst-16317	112	18	the	the	DET
ajst-16317	112	19	results	result	NOUN
ajst-16317	112	20	.	.	PUNCT
ajst-16317	113	1	this	this	DET
ajst-16317	113	2	operation	operation	NOUN
ajst-16317	113	3	can	can	AUX
ajst-16317	113	4	capture	capture	VERB
ajst-16317	113	5	the	the	DET
ajst-16317	113	6	interactive	interactive	ADJ
ajst-16317	113	7	information	information	NOUN
ajst-16317	113	8	between	between	ADP
ajst-16317	113	9	the	the	DET
ajst-16317	113	10	image	image	NOUN
ajst-16317	113	11	and	and	CCONJ
ajst-16317	113	12	the	the	DET
ajst-16317	113	13	language	language	NOUN
ajst-16317	113	14	,	,	PUNCT
ajst-16317	113	15	resulting	result	VERB
ajst-16317	113	16	in	in	ADP
ajst-16317	113	17	a	a	DET
ajst-16317	113	18	more	more	ADV
ajst-16317	113	19	accurate	accurate	ADJ
ajst-16317	113	20	similarity	similarity	NOUN
ajst-16317	113	21	measure	measure	NOUN
ajst-16317	113	22	.	.	PUNCT
ajst-16317	114	1	through	through	ADP
ajst-16317	114	2	training	training	NOUN
ajst-16317	114	3	,	,	PUNCT
ajst-16317	114	4	the	the	DET
ajst-16317	114	5	blip	blip	NOUN
ajst-16317	114	6	model	model	NOUN
ajst-16317	114	7	can	can	AUX
ajst-16317	114	8	learn	learn	VERB
ajst-16317	114	9	how	how	SCONJ
ajst-16317	114	10	to	to	PART
ajst-16317	114	11	effectively	effectively	ADV
ajst-16317	114	12	match	match	VERB
ajst-16317	114	13	images	image	NOUN
ajst-16317	114	14	and	and	CCONJ
ajst-16317	114	15	languages	language	NOUN
ajst-16317	114	16	through	through	ADP
ajst-16317	114	17	bilinear	bilinear	NOUN
ajst-16317	114	18	operations	operation	NOUN
ajst-16317	114	19	.	.	PUNCT
ajst-16317	115	1	in	in	ADP
ajst-16317	115	2	practical	practical	ADJ
ajst-16317	115	3	applications	application	NOUN
ajst-16317	115	4	,	,	PUNCT
ajst-16317	115	5	the	the	DET
ajst-16317	115	6	blip	blip	NOUN
ajst-16317	115	7	model	model	NOUN
ajst-16317	115	8	can	can	AUX
ajst-16317	115	9	use	use	VERB
ajst-16317	115	10	image	image	NOUN
ajst-16317	115	11	features	feature	NOUN
ajst-16317	115	12	and	and	CCONJ
ajst-16317	115	13	language	language	NOUN
ajst-16317	115	14	features	feature	NOUN
ajst-16317	115	15	for	for	ADP
ajst-16317	115	16	bilinear	bilinear	NOUN
ajst-16317	115	17	matching	match	VERB
ajst-16317	115	18	to	to	PART
ajst-16317	115	19	obtain	obtain	VERB
ajst-16317	115	20	a	a	DET
ajst-16317	115	21	similarity	similarity	NOUN
ajst-16317	115	22	score	score	NOUN
ajst-16317	115	23	.	.	PUNCT
ajst-16317	116	1	according	accord	VERB
ajst-16317	116	2	to	to	ADP
ajst-16317	116	3	the	the	DET
ajst-16317	116	4	task	task	NOUN
ajst-16317	116	5	requirements	requirement	NOUN
ajst-16317	116	6	,	,	PUNCT
ajst-16317	116	7	you	you	PRON
ajst-16317	116	8	can	can	AUX
ajst-16317	116	9	set	set	VERB
ajst-16317	116	10	a	a	DET
ajst-16317	116	11	threshold	threshold	NOUN
ajst-16317	116	12	to	to	PART
ajst-16317	116	13	determine	determine	VERB
ajst-16317	116	14	whether	whether	SCONJ
ajst-16317	116	15	the	the	DET
ajst-16317	116	16	match	match	NOUN
ajst-16317	116	17	is	be	AUX
ajst-16317	116	18	successful	successful	ADJ
ajst-16317	116	19	.	.	PUNCT
ajst-16317	117	1	for	for	ADP
ajst-16317	117	2	example	example	NOUN
ajst-16317	117	3	,	,	PUNCT
ajst-16317	117	4	in	in	ADP
ajst-16317	117	5	an	an	DET
ajst-16317	117	6	image	image	NOUN
ajst-16317	117	7	search	search	NOUN
ajst-16317	117	8	task	task	NOUN
ajst-16317	117	9	,	,	PUNCT
ajst-16317	117	10	if	if	SCONJ
ajst-16317	117	11	the	the	DET
ajst-16317	117	12	similarity	similarity	NOUN
ajst-16317	117	13	score	score	NOUN
ajst-16317	117	14	between	between	ADP
ajst-16317	117	15	an	an	DET
ajst-16317	117	16	image	image	NOUN
ajst-16317	117	17	and	and	CCONJ
ajst-16317	117	18	a	a	DET
ajst-16317	117	19	query	query	NOUN
ajst-16317	117	20	statement	statement	NOUN
ajst-16317	117	21	is	be	AUX
ajst-16317	117	22	higher	high	ADJ
ajst-16317	117	23	than	than	ADP
ajst-16317	117	24	a	a	DET
ajst-16317	117	25	threshold	threshold	NOUN
ajst-16317	117	26	,	,	PUNCT
ajst-16317	117	27	they	they	PRON
ajst-16317	117	28	are	be	AUX
ajst-16317	117	29	considered	consider	VERB
ajst-16317	117	30	to	to	PART
ajst-16317	117	31	be	be	AUX
ajst-16317	117	32	a	a	DET
ajst-16317	117	33	successful	successful	ADJ
ajst-16317	117	34	match	match	NOUN
ajst-16317	117	35	.	.	PUNCT
ajst-16317	118	1	to	to	PART
ajst-16317	118	2	sum	sum	VERB
ajst-16317	118	3	up	up	ADP
ajst-16317	118	4	,	,	PUNCT
ajst-16317	118	5	the	the	DET
ajst-16317	118	6	feature	feature	NOUN
ajst-16317	118	7	representation	representation	NOUN
ajst-16317	118	8	and	and	CCONJ
ajst-16317	118	9	matching	match	VERB
ajst-16317	118	10	algorithm	algorithm	NOUN
ajst-16317	118	11	of	of	ADP
ajst-16317	118	12	the	the	DET
ajst-16317	118	13	blip	blip	NOUN
ajst-16317	118	14	model	model	NOUN
ajst-16317	118	15	is	be	AUX
ajst-16317	118	16	based	base	VERB
ajst-16317	118	17	on	on	ADP
ajst-16317	118	18	the	the	DET
ajst-16317	118	19	convolutional	convolutional	ADJ
ajst-16317	118	20	neural	neural	ADJ
ajst-16317	118	21	network	network	NOUN
ajst-16317	118	22	and	and	CCONJ
ajst-16317	118	23	transformer	transformer	NOUN
ajst-16317	118	24	model	model	NOUN
ajst-16317	118	25	,	,	PUNCT
ajst-16317	118	26	the	the	DET
ajst-16317	118	27	similarity	similarity	NOUN
ajst-16317	118	28	between	between	ADP
ajst-16317	118	29	images	image	NOUN
ajst-16317	118	30	and	and	CCONJ
ajst-16317	118	31	languages	language	NOUN
ajst-16317	118	32	is	be	AUX
ajst-16317	118	33	measured	measure	VERB
ajst-16317	118	34	through	through	ADP
ajst-16317	118	35	bilinear	bilinear	NOUN
ajst-16317	118	36	matching	matching	NOUN
ajst-16317	118	37	operations	operation	NOUN
ajst-16317	118	38	to	to	PART
ajst-16317	118	39	achieve	achieve	VERB
ajst-16317	118	40	cross	cross	ADJ
ajst-16317	118	41	-	-	ADJ
ajst-16317	118	42	modal	modal	ADJ
ajst-16317	118	43	feature	feature	NOUN
ajst-16317	118	44	representation	representation	NOUN
ajst-16317	118	45	and	and	CCONJ
ajst-16317	118	46	matching	matching	NOUN
ajst-16317	118	47	.	.	PUNCT
ajst-16317	119	1	3	3	X
ajst-16317	119	2	.	.	X
ajst-16317	119	3	research	research	NOUN
ajst-16317	119	4	methods	method	NOUN
ajst-16317	119	5	and	and	CCONJ
ajst-16317	119	6	experimental	experimental	ADJ
ajst-16317	119	7	design	design	NOUN
ajst-16317	119	8	3.1	3.1	NUM
ajst-16317	119	9	.	.	PUNCT
ajst-16317	119	10	dataset	dataset	ADJ
ajst-16317	119	11	introduction	introduction	NOUN
ajst-16317	119	12	the	the	DET
ajst-16317	119	13	quality	quality	NOUN
ajst-16317	119	14	of	of	ADP
ajst-16317	119	15	the	the	DET
ajst-16317	119	16	data	datum	NOUN
ajst-16317	119	17	set	set	VERB
ajst-16317	119	18	can	can	AUX
ajst-16317	119	19	directly	directly	ADV
ajst-16317	119	20	affect	affect	VERB
ajst-16317	119	21	the	the	DET
ajst-16317	119	22	quality	quality	NOUN
ajst-16317	119	23	of	of	ADP
ajst-16317	119	24	the	the	DET
ajst-16317	119	25	training	training	NOUN
ajst-16317	119	26	model	model	NOUN
ajst-16317	119	27	parameters	parameter	NOUN
ajst-16317	119	28	.	.	PUNCT
ajst-16317	120	1	the	the	DET
ajst-16317	120	2	data	data	NOUN
ajst-16317	120	3	sets	set	NOUN
ajst-16317	120	4	used	use	VERB
ajst-16317	120	5	in	in	ADP
ajst-16317	120	6	the	the	DET
ajst-16317	120	7	experimental	experimental	ADJ
ajst-16317	120	8	part	part	NOUN
ajst-16317	120	9	are	be	AUX
ajst-16317	120	10	:	:	PUNCT
ajst-16317	120	11	coco_karpathy_train	coco_karpathy_train	PROPN
ajst-16317	120	12	,	,	PUNCT
ajst-16317	120	13	coco_karpathy_caption_eval	coco_karpathy_caption_eval	NOUN
ajst-16317	120	14	,	,	PUNCT
ajst-16317	120	15	coco_karpathy_retrieval_eval	coco_karpathy_retrieval_eval	NOUN
ajst-16317	120	16	,	,	PUNCT
ajst-16317	120	17	nocaps_eval	nocaps_eval	NOUN
ajst-16317	120	18	,	,	PUNCT
ajst-16317	120	19	flickr30k_train	flickr30k_train	ADJ
ajst-16317	120	20	and	and	CCONJ
ajst-16317	120	21	flickr30k_retrieval_eval	flickr30k_retrieval_eval	PROPN
ajst-16317	120	22	,	,	PUNCT
ajst-16317	120	23	it	it	PRON
ajst-16317	120	24	is	be	AUX
ajst-16317	120	25	a	a	DET
ajst-16317	120	26	data	data	NOUN
ajst-16317	120	27	set	set	VERB
ajst-16317	120	28	for	for	ADP
ajst-16317	120	29	image	image	NOUN
ajst-16317	120	30	annotation	annotation	NOUN
ajst-16317	120	31	and	and	CCONJ
ajst-16317	120	32	image	image	NOUN
ajst-16317	120	33	retrieval	retrieval	NOUN
ajst-16317	120	34	tasks	task	NOUN
ajst-16317	120	35	.	.	PUNCT
ajst-16317	121	1	vqa_dataset	vqa_dataset	NOUN
ajst-16317	121	2	can	can	AUX
ajst-16317	121	3	be	be	AUX
ajst-16317	121	4	used	use	VERB
ajst-16317	121	5	for	for	ADP
ajst-16317	121	6	visual	visual	ADJ
ajst-16317	121	7	question	question	NOUN
ajst-16317	121	8	answering	answering	NOUN
ajst-16317	121	9	tasks	task	NOUN
ajst-16317	121	10	;	;	PUNCT
ajst-16317	121	11	nlvr_dataset	nlvr_dataset	NUM
ajst-16317	121	12	can	can	AUX
ajst-16317	121	13	be	be	AUX
ajst-16317	121	14	used	use	VERB
ajst-16317	121	15	for	for	ADP
ajst-16317	121	16	natural	natural	ADJ
ajst-16317	121	17	language	language	NOUN
ajst-16317	121	18	reasoning	reasoning	NOUN
ajst-16317	121	19	tasks	task	NOUN
ajst-16317	121	20	;	;	PUNCT
ajst-16317	121	21	pretrain_dataset	pretrain_dataset	NOUN
ajst-16317	121	22	is	be	AUX
ajst-16317	121	23	the	the	DET
ajst-16317	121	24	data	datum	NOUN
ajst-16317	121	25	set	set	VERB
ajst-16317	121	26	used	use	VERB
ajst-16317	121	27	for	for	ADP
ajst-16317	121	28	language	language	NOUN
ajst-16317	121	29	model	model	NOUN
ajst-16317	121	30	pretraining.pre	pretraining.pre	NOUN
ajst-16317	121	31	-	-	NOUN
ajst-16317	121	32	training	training	NOUN
ajst-16317	121	33	datasets	dataset	NOUN
ajst-16317	121	34	often	often	ADV
ajst-16317	121	35	contain	contain	VERB
ajst-16317	121	36	large	large	ADJ
ajst-16317	121	37	amounts	amount	NOUN
ajst-16317	121	38	of	of	ADP
ajst-16317	121	39	unlabeled	unlabeled	ADJ
ajst-16317	121	40	image	image	NOUN
ajst-16317	121	41	and	and	CCONJ
ajst-16317	121	42	text	text	NOUN
ajst-16317	121	43	data	datum	NOUN
ajst-16317	121	44	.	.	PUNCT
ajst-16317	122	1	for	for	ADP
ajst-16317	122	2	example	example	NOUN
ajst-16317	122	3	,	,	PUNCT
ajst-16317	122	4	the	the	DET
ajst-16317	122	5	coco	coco	PROPN
ajst-16317	122	6	dataset	dataset	PROPN
ajst-16317	122	7	contains	contain	VERB
ajst-16317	122	8	more	more	ADJ
ajst-16317	122	9	than	than	ADP
ajst-16317	122	10	330,000	330,000	NUM
ajst-16317	122	11	images	image	NOUN
ajst-16317	122	12	and	and	CCONJ
ajst-16317	122	13	annotations	annotation	NOUN
ajst-16317	122	14	of	of	ADP
ajst-16317	122	15	multiple	multiple	ADJ
ajst-16317	122	16	object	object	NOUN
ajst-16317	122	17	instances	instance	NOUN
ajst-16317	122	18	,	,	PUNCT
ajst-16317	122	19	etc	etc	X
ajst-16317	122	20	.	.	X
ajst-16317	123	1	pre	pre	ADJ
ajst-16317	123	2	-	-	ADJ
ajst-16317	123	3	training	training	ADJ
ajst-16317	123	4	datasets	dataset	NOUN
ajst-16317	123	5	are	be	AUX
ajst-16317	123	6	used	use	VERB
ajst-16317	123	7	to	to	PART
ajst-16317	123	8	train	train	VERB
ajst-16317	123	9	image	image	NOUN
ajst-16317	123	10	and	and	CCONJ
ajst-16317	123	11	text	text	NOUN
ajst-16317	123	12	models	model	NOUN
ajst-16317	123	13	to	to	PART
ajst-16317	123	14	learn	learn	VERB
ajst-16317	123	15	richer	rich	ADJ
ajst-16317	123	16	visual	visual	ADJ
ajst-16317	123	17	and	and	CCONJ
ajst-16317	123	18	semantic	semantic	ADJ
ajst-16317	123	19	features	feature	NOUN
ajst-16317	123	20	.	.	PUNCT
ajst-16317	124	1	by	by	ADP
ajst-16317	124	2	using	use	VERB
ajst-16317	124	3	pre	pre	ADJ
ajst-16317	124	4	-	-	ADJ
ajst-16317	124	5	trained	train	VERB
ajst-16317	124	6	models	model	NOUN
ajst-16317	124	7	,	,	PUNCT
ajst-16317	124	8	you	you	PRON
ajst-16317	124	9	can	can	AUX
ajst-16317	124	10	improve	improve	VERB
ajst-16317	124	11	model	model	NOUN
ajst-16317	124	12	performance	performance	NOUN
ajst-16317	124	13	in	in	ADP
ajst-16317	124	14	a	a	DET
ajst-16317	124	15	variety	variety	NOUN
ajst-16317	124	16	of	of	ADP
ajst-16317	124	17	visual	visual	ADJ
ajst-16317	124	18	and	and	CCONJ
ajst-16317	124	19	text	text	NOUN
ajst-16317	124	20	tasks	task	NOUN
ajst-16317	124	21	.	.	PUNCT
ajst-16317	125	1	image	image	NOUN
ajst-16317	125	2	retrieval	retrieval	NOUN
ajst-16317	125	3	data	datum	NOUN
ajst-16317	125	4	set	set	NOUN
ajst-16317	125	5	(	(	PUNCT
ajst-16317	125	6	coco	coco	PROPN
ajst-16317	125	7	,	,	PUNCT
ajst-16317	125	8	flickr30k	flickr30k	PROPN
ajst-16317	125	9	):	):	PUNCT
ajst-16317	125	10	image	image	NOUN
ajst-16317	125	11	retrieval	retrieval	NOUN
ajst-16317	125	12	datasets	dataset	NOUN
ajst-16317	125	13	contain	contain	VERB
ajst-16317	125	14	a	a	DET
ajst-16317	125	15	large	large	ADJ
ajst-16317	125	16	number	number	NOUN
ajst-16317	125	17	of	of	ADP
ajst-16317	125	18	images	image	NOUN
ajst-16317	125	19	and	and	CCONJ
ajst-16317	125	20	annotation	annotation	NOUN
ajst-16317	125	21	information	information	NOUN
ajst-16317	125	22	associated	associate	VERB
ajst-16317	125	23	with	with	ADP
ajst-16317	125	24	them	they	PRON
ajst-16317	125	25	,	,	PUNCT
ajst-16317	125	26	and	and	CCONJ
ajst-16317	125	27	the	the	DET
ajst-16317	125	28	flickr30k	flickr30k	ADJ
ajst-16317	125	29	dataset	dataset	NOUN
ajst-16317	125	30	has	have	AUX
ajst-16317	125	31	become	become	VERB
ajst-16317	125	32	a	a	DET
ajst-16317	125	33	standard	standard	ADJ
ajst-16317	125	34	benchmark	benchmark	NOUN
ajst-16317	125	35	for	for	ADP
ajst-16317	125	36	sentence	sentence	NOUN
ajst-16317	125	37	-	-	PUNCT
ajst-16317	125	38	based	base	VERB
ajst-16317	125	39	image	image	NOUN
ajst-16317	125	40	description	description	NOUN
ajst-16317	125	41	.	.	PUNCT
ajst-16317	126	1	it	it	PRON
ajst-16317	126	2	augments	augment	VERB
ajst-16317	126	3	158k	158k	NUM
ajst-16317	126	4	captions	caption	NOUN
ajst-16317	126	5	from	from	ADP
ajst-16317	126	6	flickr30k	flickr30k	PROPN
ajst-16317	126	7	with	with	ADP
ajst-16317	126	8	244k	244k	PROPN
ajst-16317	126	9	coreference	coreference	NOUN
ajst-16317	126	10	chains	chain	NOUN
ajst-16317	126	11	linking	link	VERB
ajst-16317	126	12	the	the	DET
ajst-16317	126	13	same	same	ADJ
ajst-16317	126	14	entities	entity	NOUN
ajst-16317	126	15	mentioned	mention	VERB
ajst-16317	126	16	in	in	ADP
ajst-16317	126	17	different	different	ADJ
ajst-16317	126	18	captions	caption	NOUN
ajst-16317	126	19	for	for	ADP
ajst-16317	126	20	the	the	DET
ajst-16317	126	21	same	same	ADJ
ajst-16317	126	22	image	image	NOUN
ajst-16317	126	23	and	and	CCONJ
ajst-16317	126	24	associating	associate	VERB
ajst-16317	126	25	them	they	PRON
ajst-16317	126	26	with	with	ADP
ajst-16317	126	27	276k	276k	PROPN
ajst-16317	126	28	manually	manually	ADV
ajst-16317	126	29	annotated	annotate	VERB
ajst-16317	126	30	bounding	bounding	NOUN
ajst-16317	126	31	boxes	box	NOUN
ajst-16317	126	32	.	.	PUNCT
ajst-16317	127	1	this	this	DET
ajst-16317	127	2	annotation	annotation	NOUN
ajst-16317	127	3	is	be	AUX
ajst-16317	127	4	critical	critical	ADJ
ajst-16317	127	5	for	for	ADP
ajst-16317	127	6	continued	continue	VERB
ajst-16317	127	7	advances	advance	NOUN
ajst-16317	127	8	in	in	ADP
ajst-16317	127	9	automatic	automatic	ADJ
ajst-16317	127	10	image	image	NOUN
ajst-16317	127	11	description	description	NOUN
ajst-16317	127	12	and	and	CCONJ
ajst-16317	127	13	underlying	underlying	ADJ
ajst-16317	127	14	language	language	NOUN
ajst-16317	127	15	understanding	understanding	NOUN
ajst-16317	127	16	.	.	PUNCT
ajst-16317	128	1	they	they	PRON
ajst-16317	128	2	allow	allow	VERB
ajst-16317	128	3	us	we	PRON
ajst-16317	128	4	to	to	PART
ajst-16317	128	5	define	define	VERB
ajst-16317	128	6	a	a	DET
ajst-16317	128	7	new	new	ADJ
ajst-16317	128	8	benchmark	benchmark	NOUN
ajst-16317	128	9	for	for	ADP
ajst-16317	128	10	the	the	DET
ajst-16317	128	11	localization	localization	NOUN
ajst-16317	128	12	of	of	ADP
ajst-16317	128	13	textual	textual	ADJ
ajst-16317	128	14	entity	entity	NOUN
ajst-16317	128	15	mentions	mention	NOUN
ajst-16317	128	16	in	in	ADP
ajst-16317	128	17	images	image	NOUN
ajst-16317	128	18	,	,	PUNCT
ajst-16317	128	19	which	which	PRON
ajst-16317	128	20	combines	combine	VERB
ajst-16317	128	21	image	image	NOUN
ajst-16317	128	22	-	-	PUNCT
ajst-16317	128	23	text	text	NOUN
ajst-16317	128	24	embeddings	embedding	NOUN
ajst-16317	128	25	,	,	PUNCT
ajst-16317	128	26	detectors	detector	NOUN
ajst-16317	128	27	for	for	ADP
ajst-16317	128	28	common	common	ADJ
ajst-16317	128	29	objects	object	NOUN
ajst-16317	128	30	,	,	PUNCT
ajst-16317	128	31	color	color	NOUN
ajst-16317	128	32	classifiers	classifier	NOUN
ajst-16317	128	33	,	,	PUNCT
ajst-16317	128	34	and	and	CCONJ
ajst-16317	128	35	biases	bias	NOUN
ajst-16317	128	36	against	against	ADP
ajst-16317	128	37	the	the	DET
ajst-16317	128	38	selection	selection	NOUN
ajst-16317	128	39	of	of	ADP
ajst-16317	128	40	larger	large	ADJ
ajst-16317	128	41	objects	object	NOUN
ajst-16317	128	42	.	.	PUNCT
ajst-16317	129	1	3.2	3.2	NUM
ajst-16317	129	2	.	.	PUNCT
ajst-16317	130	1	feature	feature	NOUN
ajst-16317	130	2	extraction	extraction	NOUN
ajst-16317	130	3	method	method	NOUN
ajst-16317	130	4	based	base	VERB
ajst-16317	130	5	on	on	ADP
ajst-16317	130	6	blip	blip	NOUN
ajst-16317	130	7	model	model	NOUN
ajst-16317	130	8	the	the	DET
ajst-16317	130	9	feature	feature	NOUN
ajst-16317	130	10	extraction	extraction	NOUN
ajst-16317	130	11	method	method	NOUN
ajst-16317	130	12	based	base	VERB
ajst-16317	130	13	on	on	ADP
ajst-16317	130	14	the	the	DET
ajst-16317	130	15	blip	blip	NOUN
ajst-16317	130	16	model	model	NOUN
ajst-16317	130	17	is	be	AUX
ajst-16317	130	18	to	to	PART
ajst-16317	130	19	input	input	VERB
ajst-16317	130	20	images	image	NOUN
ajst-16317	130	21	and	and	CCONJ
ajst-16317	130	22	text	text	NOUN
ajst-16317	130	23	into	into	ADP
ajst-16317	130	24	the	the	DET
ajst-16317	130	25	blip	blip	NOUN
ajst-16317	130	26	model	model	NOUN
ajst-16317	130	27	and	and	CCONJ
ajst-16317	130	28	use	use	VERB
ajst-16317	130	29	the	the	DET
ajst-16317	130	30	output	output	NOUN
ajst-16317	130	31	of	of	ADP
ajst-16317	130	32	the	the	DET
ajst-16317	130	33	model	model	NOUN
ajst-16317	130	34	as	as	ADP
ajst-16317	130	35	feature	feature	NOUN
ajst-16317	130	36	representation	representation	NOUN
ajst-16317	130	37	of	of	ADP
ajst-16317	130	38	the	the	DET
ajst-16317	130	39	image	image	NOUN
ajst-16317	130	40	and	and	CCONJ
ajst-16317	130	41	text	text	NOUN
ajst-16317	130	42	.	.	PUNCT
ajst-16317	131	1	the	the	DET
ajst-16317	131	2	blip	blip	NOUN
ajst-16317	131	3	model	model	NOUN
ajst-16317	131	4	is	be	AUX
ajst-16317	131	5	a	a	DET
ajst-16317	131	6	multi	multi	ADJ
ajst-16317	131	7	-	-	ADJ
ajst-16317	131	8	modal	modal	ADJ
ajst-16317	131	9	pre	pre	ADJ
ajst-16317	131	10	-	-	ADJ
ajst-16317	131	11	trained	train	VERB
ajst-16317	131	12	model	model	NOUN
ajst-16317	131	13	designed	design	VERB
ajst-16317	131	14	to	to	PART
ajst-16317	131	15	learn	learn	VERB
ajst-16317	131	16	semantic	semantic	ADJ
ajst-16317	131	17	associations	association	NOUN
ajst-16317	131	18	between	between	ADP
ajst-16317	131	19	images	image	NOUN
ajst-16317	131	20	and	and	CCONJ
ajst-16317	131	21	text	text	NOUN
ajst-16317	131	22	.	.	PUNCT
ajst-16317	132	1	it	it	PRON
ajst-16317	132	2	consists	consist	VERB
ajst-16317	132	3	of	of	ADP
ajst-16317	132	4	two	two	NUM
ajst-16317	132	5	sub	sub	NOUN
ajst-16317	132	6	-	-	NOUN
ajst-16317	132	7	models	model	NOUN
ajst-16317	132	8	:	:	PUNCT
ajst-16317	132	9	image	image	NOUN
ajst-16317	132	10	-	-	PUNCT
ajst-16317	132	11	text	text	NOUN
ajst-16317	132	12	matching	matching	NOUN
ajst-16317	132	13	(	(	PUNCT
ajst-16317	132	14	itm	itm	NOUN
ajst-16317	132	15	)	)	PUNCT
ajst-16317	132	16	model	model	NOUN
ajst-16317	132	17	and	and	CCONJ
ajst-16317	132	18	visual	visual	ADJ
ajst-16317	132	19	question	question	NOUN
ajst-16317	132	20	answering	answer	VERB
ajst-16317	132	21	(	(	PUNCT
ajst-16317	132	22	vqa	vqa	ADJ
ajst-16317	132	23	)	)	PUNCT
ajst-16317	132	24	model	model	NOUN
ajst-16317	132	25	.	.	PUNCT
ajst-16317	133	1	image	image	NOUN
ajst-16317	133	2	to	to	ADP
ajst-16317	133	3	text	text	NOUN
ajst-16317	133	4	matching	matching	NOUN
ajst-16317	133	5	:	:	PUNCT
ajst-16317	133	6	first	first	ADV
ajst-16317	133	7	,	,	PUNCT
ajst-16317	133	8	the	the	DET
ajst-16317	133	9	neural	neural	ADJ
ajst-16317	133	10	network	network	NOUN
ajst-16317	133	11	model	model	NOUN
ajst-16317	133	12	of	of	ADP
ajst-16317	133	13	blip_itm	blip_itm	PROPN
ajst-16317	133	14	is	be	AUX
ajst-16317	133	15	defined	define	VERB
ajst-16317	133	16	,	,	PUNCT
ajst-16317	133	17	which	which	PRON
ajst-16317	133	18	combines	combine	VERB
ajst-16317	133	19	a	a	DET
ajst-16317	133	20	visual	visual	ADJ
ajst-16317	133	21	transformer	transformer	NOUN
ajst-16317	133	22	and	and	CCONJ
ajst-16317	133	23	a	a	DET
ajst-16317	133	24	text	text	NOUN
ajst-16317	133	25	encoder	encoder	NOUN
ajst-16317	133	26	to	to	PART
ajst-16317	133	27	handle	handle	VERB
ajst-16317	133	28	the	the	DET
ajst-16317	133	29	matching	matching	NOUN
ajst-16317	133	30	task	task	NOUN
ajst-16317	133	31	between	between	ADP
ajst-16317	133	32	images	image	NOUN
ajst-16317	133	33	and	and	CCONJ
ajst-16317	133	34	text	text	NOUN
ajst-16317	133	35	.	.	PUNCT
ajst-16317	134	1	specifically	specifically	ADV
ajst-16317	134	2	:	:	PUNCT
ajst-16317	134	3	the	the	DET
ajst-16317	134	4	model	model	NOUN
ajst-16317	134	5	includes	include	VERB
ajst-16317	134	6	a	a	DET
ajst-16317	134	7	visual	visual	ADJ
ajst-16317	134	8	encoder	encoder	NOUN
ajst-16317	134	9	(	(	PUNCT
ajst-16317	134	10	visual_encoder	visual_encoder	PROPN
ajst-16317	134	11	)	)	PUNCT
ajst-16317	134	12	and	and	CCONJ
ajst-16317	134	13	a	a	DET
ajst-16317	134	14	text	text	NOUN
ajst-16317	134	15	encoder	encoder	NOUN
ajst-16317	134	16	(	(	PUNCT
ajst-16317	134	17	text_encoder	text_encoder	PROPN
ajst-16317	134	18	)	)	PUNCT
ajst-16317	134	19	,	,	PUNCT
ajst-16317	134	20	which	which	PRON
ajst-16317	134	21	are	be	AUX
ajst-16317	134	22	used	use	VERB
ajst-16317	134	23	to	to	PART
ajst-16317	134	24	process	process	VERB
ajst-16317	134	25	input	input	NOUN
ajst-16317	134	26	images	image	NOUN
ajst-16317	134	27	and	and	CCONJ
ajst-16317	134	28	text	text	NOUN
ajst-16317	134	29	respectively	respectively	ADV
ajst-16317	134	30	.	.	PUNCT
ajst-16317	135	1	the	the	DET
ajst-16317	135	2	visual	visual	ADJ
ajst-16317	135	3	encoder	encoder	NOUN
ajst-16317	135	4	uses	use	VERB
ajst-16317	135	5	a	a	DET
ajst-16317	135	6	visual	visual	ADJ
ajst-16317	135	7	transformer	transformer	NOUN
ajst-16317	135	8	(	(	PUNCT
ajst-16317	135	9	vision	vision	NOUN
ajst-16317	135	10	transformer	transformer	NOUN
ajst-16317	135	11	,	,	PUNCT
ajst-16317	135	12	vit	vit	NOUN
ajst-16317	135	13	)	)	PUNCT
ajst-16317	135	14	to	to	PART
ajst-16317	135	15	encode	encode	VERB
ajst-16317	135	16	the	the	DET
ajst-16317	135	17	input	input	NOUN
ajst-16317	135	18	image	image	NOUN
ajst-16317	135	19	and	and	CCONJ
ajst-16317	135	20	obtain	obtain	VERB
ajst-16317	135	21	the	the	DET
ajst-16317	135	22	embedded	embed	VERB
ajst-16317	135	23	representation	representation	NOUN
ajst-16317	135	24	of	of	ADP
ajst-16317	135	25	the	the	DET
ajst-16317	135	26	image	image	NOUN
ajst-16317	135	27	.	.	PUNCT
ajst-16317	136	1	the	the	DET
ajst-16317	136	2	text	text	NOUN
ajst-16317	136	3	encoder	encoder	NOUN
ajst-16317	136	4	uses	use	VERB
ajst-16317	136	5	the	the	DET
ajst-16317	136	6	bert	bert	PROPN
ajst-16317	136	7	model	model	NOUN
ajst-16317	136	8	to	to	PART
ajst-16317	136	9	encode	encode	VERB
ajst-16317	136	10	the	the	DET
ajst-16317	136	11	input	input	NOUN
ajst-16317	136	12	text	text	NOUN
ajst-16317	136	13	and	and	CCONJ
ajst-16317	136	14	obtain	obtain	VERB
ajst-16317	136	15	the	the	DET
ajst-16317	136	16	84	84	NUM
ajst-16317	136	17	embedded	embed	VERB
ajst-16317	136	18	representation	representation	NOUN
ajst-16317	136	19	of	of	ADP
ajst-16317	136	20	the	the	DET
ajst-16317	136	21	text	text	NOUN
ajst-16317	136	22	.	.	PUNCT
ajst-16317	137	1	the	the	DET
ajst-16317	137	2	model	model	NOUN
ajst-16317	137	3	also	also	ADV
ajst-16317	137	4	includes	include	VERB
ajst-16317	137	5	some	some	DET
ajst-16317	137	6	linear	linear	ADJ
ajst-16317	137	7	projection	projection	NOUN
ajst-16317	137	8	layers	layer	NOUN
ajst-16317	137	9	(	(	PUNCT
ajst-16317	137	10	vision_proj	vision_proj	NUM
ajst-16317	137	11	,	,	PUNCT
ajst-16317	137	12	text_proj	text_proj	NUM
ajst-16317	137	13	)	)	PUNCT
ajst-16317	137	14	and	and	CCONJ
ajst-16317	137	15	a	a	DET
ajst-16317	137	16	linear	linear	ADJ
ajst-16317	137	17	classification	classification	NOUN
ajst-16317	137	18	head	head	NOUN
ajst-16317	137	19	(	(	PUNCT
ajst-16317	137	20	itm_head	itm_head	NOUN
ajst-16317	137	21	)	)	PUNCT
ajst-16317	137	22	for	for	ADP
ajst-16317	137	23	mapping	map	VERB
ajst-16317	137	24	the	the	DET
ajst-16317	137	25	embedded	embed	VERB
ajst-16317	137	26	representations	representation	NOUN
ajst-16317	137	27	of	of	ADP
ajst-16317	137	28	images	image	NOUN
ajst-16317	137	29	and	and	CCONJ
ajst-16317	137	30	text	text	NOUN
ajst-16317	137	31	into	into	ADP
ajst-16317	137	32	the	the	DET
ajst-16317	137	33	same	same	ADJ
ajst-16317	137	34	space	space	NOUN
ajst-16317	137	35	and	and	CCONJ
ajst-16317	137	36	performing	perform	VERB
ajst-16317	137	37	matching	matching	NOUN
ajst-16317	137	38	tasks	task	NOUN
ajst-16317	137	39	.	.	PUNCT
ajst-16317	138	1	the	the	DET
ajst-16317	138	2	forward	forward	ADJ
ajst-16317	138	3	method	method	NOUN
ajst-16317	138	4	of	of	ADP
ajst-16317	138	5	the	the	DET
ajst-16317	138	6	model	model	NOUN
ajst-16317	138	7	performs	perform	VERB
ajst-16317	138	8	different	different	ADJ
ajst-16317	138	9	tasks	task	NOUN
ajst-16317	138	10	according	accord	VERB
ajst-16317	138	11	to	to	ADP
ajst-16317	138	12	different	different	ADJ
ajst-16317	138	13	matching	matching	NOUN
ajst-16317	138	14	heads	head	NOUN
ajst-16317	138	15	(	(	PUNCT
ajst-16317	138	16	match_head	match_head	PROPN
ajst-16317	138	17	)	)	PUNCT
ajst-16317	138	18	,	,	PUNCT
ajst-16317	138	19	including	include	VERB
ajst-16317	138	20	image	image	NOUN
ajst-16317	138	21	-	-	PUNCT
ajst-16317	138	22	text	text	NOUN
ajst-16317	138	23	matching	matching	NOUN
ajst-16317	138	24	(	(	PUNCT
ajst-16317	138	25	itm	itm	NOUN
ajst-16317	138	26	)	)	PUNCT
ajst-16317	138	27	and	and	CCONJ
ajst-16317	138	28	image	image	NOUN
ajst-16317	138	29	-	-	PUNCT
ajst-16317	138	30	text	text	NOUN
ajst-16317	138	31	cosine	cosine	NOUN
ajst-16317	138	32	similarity	similarity	NOUN
ajst-16317	138	33	calculation	calculation	NOUN
ajst-16317	138	34	(	(	PUNCT
ajst-16317	138	35	itc	itc	PROPN
ajst-16317	138	36	)	)	PUNCT
ajst-16317	138	37	.	.	PUNCT
ajst-16317	139	1	visual	visual	ADJ
ajst-16317	139	2	q&a	q&a	PROPN
ajst-16317	139	3	:	:	PUNCT
ajst-16317	139	4	in	in	ADP
ajst-16317	139	5	the	the	DET
ajst-16317	139	6	experiment	experiment	NOUN
ajst-16317	139	7	,	,	PUNCT
ajst-16317	139	8	the	the	DET
ajst-16317	139	9	model	model	NOUN
ajst-16317	139	10	blip_vqa	blip_vqa	PROPN
ajst-16317	139	11	was	be	AUX
ajst-16317	139	12	defined	define	VERB
ajst-16317	139	13	based	base	VERB
ajst-16317	139	14	on	on	ADP
ajst-16317	139	15	the	the	DET
ajst-16317	139	16	visual	visual	ADJ
ajst-16317	139	17	question	question	NOUN
ajst-16317	139	18	answering	answering	NOUN
ajst-16317	139	19	task	task	NOUN
ajst-16317	139	20	.	.	PUNCT
ajst-16317	140	1	the	the	DET
ajst-16317	140	2	model	model	NOUN
ajst-16317	140	3	uses	use	VERB
ajst-16317	140	4	a	a	DET
ajst-16317	140	5	hybrid	hybrid	ADJ
ajst-16317	140	6	encoder	encoder	NOUN
ajst-16317	140	7	-	-	PUNCT
ajst-16317	140	8	decoder	decoder	NOUN
ajst-16317	140	9	model	model	NOUN
ajst-16317	140	10	,	,	PUNCT
ajst-16317	140	11	which	which	PRON
ajst-16317	140	12	includes	include	VERB
ajst-16317	140	13	an	an	DET
ajst-16317	140	14	image	image	NOUN
ajst-16317	140	15	encoder	encoder	NOUN
ajst-16317	140	16	and	and	CCONJ
ajst-16317	140	17	a	a	DET
ajst-16317	140	18	text	text	NOUN
ajst-16317	140	19	encoder	encoder	NOUN
ajst-16317	140	20	.	.	PUNCT
ajst-16317	141	1	in	in	ADP
ajst-16317	141	2	the	the	DET
ajst-16317	141	3	constructor	constructor	NOUN
ajst-16317	141	4	of	of	ADP
ajst-16317	141	5	the	the	DET
ajst-16317	141	6	model	model	NOUN
ajst-16317	141	7	,	,	PUNCT
ajst-16317	141	8	a	a	DET
ajst-16317	141	9	visual	visual	ADJ
ajst-16317	141	10	encoder	encoder	NOUN
ajst-16317	141	11	(	(	PUNCT
ajst-16317	141	12	visual_encoder	visual_encoder	NOUN
ajst-16317	141	13	)	)	PUNCT
ajst-16317	141	14	is	be	AUX
ajst-16317	141	15	first	first	ADV
ajst-16317	141	16	created	create	VERB
ajst-16317	141	17	,	,	PUNCT
ajst-16317	141	18	which	which	PRON
ajst-16317	141	19	is	be	AUX
ajst-16317	141	20	a	a	DET
ajst-16317	141	21	visual	visual	ADJ
ajst-16317	141	22	transformer	transformer	NOUN
ajst-16317	141	23	model	model	NOUN
ajst-16317	141	24	(	(	PUNCT
ajst-16317	141	25	vision	vision	NOUN
ajst-16317	141	26	transformer	transformer	NOUN
ajst-16317	141	27	)	)	PUNCT
ajst-16317	141	28	,	,	PUNCT
ajst-16317	141	29	used	use	VERB
ajst-16317	141	30	to	to	PART
ajst-16317	141	31	convert	convert	VERB
ajst-16317	141	32	input	input	NOUN
ajst-16317	141	33	images	image	NOUN
ajst-16317	141	34	into	into	ADP
ajst-16317	141	35	image	image	NOUN
ajst-16317	141	36	embeddings	embedding	NOUN
ajst-16317	141	37	(	(	PUNCT
ajst-16317	141	38	image_embeds	image_embed	NOUN
ajst-16317	141	39	)	)	PUNCT
ajst-16317	141	40	.	.	PUNCT
ajst-16317	142	1	then	then	ADV
ajst-16317	142	2	,	,	PUNCT
ajst-16317	142	3	a	a	DET
ajst-16317	142	4	text	text	NOUN
ajst-16317	142	5	encoder	encoder	NOUN
ajst-16317	142	6	(	(	PUNCT
ajst-16317	142	7	text_encoder	text_encoder	PROPN
ajst-16317	142	8	)	)	PUNCT
ajst-16317	142	9	was	be	AUX
ajst-16317	142	10	created	create	VERB
ajst-16317	142	11	,	,	PUNCT
ajst-16317	142	12	which	which	PRON
ajst-16317	142	13	is	be	AUX
ajst-16317	142	14	a	a	DET
ajst-16317	142	15	text	text	NOUN
ajst-16317	142	16	encoder	encoder	NOUN
ajst-16317	142	17	based	base	VERB
ajst-16317	142	18	on	on	ADP
ajst-16317	142	19	the	the	DET
ajst-16317	142	20	bert	bert	PROPN
ajst-16317	142	21	model	model	NOUN
ajst-16317	142	22	(	(	PUNCT
ajst-16317	142	23	bertmodel	bertmodel	NOUN
ajst-16317	142	24	)	)	PUNCT
ajst-16317	142	25	.	.	PUNCT
ajst-16317	143	1	finally	finally	ADV
ajst-16317	143	2	,	,	PUNCT
ajst-16317	143	3	a	a	DET
ajst-16317	143	4	text	text	NOUN
ajst-16317	143	5	decoder	decoder	NOUN
ajst-16317	143	6	(	(	PUNCT
ajst-16317	143	7	text_decoder	text_decoder	NOUN
ajst-16317	143	8	)	)	PUNCT
ajst-16317	143	9	is	be	AUX
ajst-16317	143	10	created	create	VERB
ajst-16317	143	11	,	,	PUNCT
ajst-16317	143	12	which	which	PRON
ajst-16317	143	13	is	be	AUX
ajst-16317	143	14	also	also	ADV
ajst-16317	143	15	a	a	DET
ajst-16317	143	16	text	text	NOUN
ajst-16317	143	17	decoder	decoder	NOUN
ajst-16317	143	18	based	base	VERB
ajst-16317	143	19	on	on	ADP
ajst-16317	143	20	the	the	DET
ajst-16317	143	21	bert	bert	PROPN
ajst-16317	143	22	model	model	PROPN
ajst-16317	143	23	(	(	PUNCT
ajst-16317	143	24	bertlmheadmodel	bertlmheadmodel	NOUN
ajst-16317	143	25	)	)	PUNCT
ajst-16317	143	26	.	.	PUNCT
ajst-16317	144	1	3.3	3.3	NUM
ajst-16317	144	2	.	.	PUNCT
ajst-16317	145	1	two	two	NUM
ajst-16317	145	2	major	major	ADJ
ajst-16317	145	3	loss	loss	NOUN
ajst-16317	145	4	functions	function	NOUN
ajst-16317	145	5	3.3.1	3.3.1	NUM
ajst-16317	145	6	.	.	PUNCT
ajst-16317	146	1	contrast	contrast	NOUN
ajst-16317	146	2	learning	learn	VERB
ajst-16317	146	3	loss	loss	NOUN
ajst-16317	146	4	function	function	NOUN
ajst-16317	146	5	nt	not	PART
ajst-16317	146	6	-	-	PUNCT
ajst-16317	146	7	xent	xent	ADJ
ajst-16317	146	8	loss	loss	NOUN
ajst-16317	146	9	is	be	AUX
ajst-16317	146	10	a	a	DET
ajst-16317	146	11	commonly	commonly	ADV
ajst-16317	146	12	used	use	VERB
ajst-16317	146	13	contrastive	contrastive	ADJ
ajst-16317	146	14	learning	learning	NOUN
ajst-16317	146	15	loss	loss	NOUN
ajst-16317	146	16	function	function	NOUN
ajst-16317	146	17	,	,	PUNCT
ajst-16317	146	18	whose	whose	DET
ajst-16317	146	19	full	full	ADJ
ajst-16317	146	20	name	name	NOUN
ajst-16317	146	21	is	be	AUX
ajst-16317	146	22	normalized	normalize	VERB
ajst-16317	146	23	temperature	temperature	NOUN
ajst-16317	146	24	-	-	PUNCT
ajst-16317	146	25	scaled	scale	VERB
ajst-16317	146	26	cross	cross	NOUN
ajst-16317	146	27	entropy	entropy	PROPN
ajst-16317	146	28	loss	loss	PROPN
ajst-16317	146	29	.	.	PUNCT
ajst-16317	147	1	the	the	DET
ajst-16317	147	2	goal	goal	NOUN
ajst-16317	147	3	of	of	ADP
ajst-16317	147	4	contrastive	contrastive	ADJ
ajst-16317	147	5	learning	learning	NOUN
ajst-16317	147	6	is	be	AUX
ajst-16317	147	7	to	to	PART
ajst-16317	147	8	learn	learn	VERB
ajst-16317	147	9	a	a	DET
ajst-16317	147	10	good	good	ADJ
ajst-16317	147	11	feature	feature	NOUN
ajst-16317	147	12	representation	representation	NOUN
ajst-16317	147	13	by	by	ADP
ajst-16317	147	14	maximizing	maximize	VERB
ajst-16317	147	15	the	the	DET
ajst-16317	147	16	similarity	similarity	NOUN
ajst-16317	147	17	between	between	ADP
ajst-16317	147	18	similar	similar	ADJ
ajst-16317	147	19	samples	sample	NOUN
ajst-16317	147	20	and	and	CCONJ
ajst-16317	147	21	minimizing	minimize	VERB
ajst-16317	147	22	the	the	DET
ajst-16317	147	23	similarity	similarity	NOUN
ajst-16317	147	24	between	between	ADP
ajst-16317	147	25	dissimilar	dissimilar	ADJ
ajst-16317	147	26	samples	sample	NOUN
ajst-16317	147	27	.	.	PUNCT
ajst-16317	148	1	when	when	SCONJ
ajst-16317	148	2	using	use	VERB
ajst-16317	148	3	nt	not	PART
ajst-16317	148	4	-	-	PUNCT
ajst-16317	148	5	xent	xent	ADJ
ajst-16317	148	6	loss	loss	NOUN
ajst-16317	148	7	,	,	PUNCT
ajst-16317	148	8	the	the	DET
ajst-16317	148	9	model	model	NOUN
ajst-16317	148	10	treats	treat	VERB
ajst-16317	148	11	each	each	DET
ajst-16317	148	12	sample	sample	NOUN
ajst-16317	148	13	as	as	ADP
ajst-16317	148	14	a	a	DET
ajst-16317	148	15	separate	separate	ADJ
ajst-16317	148	16	category	category	NOUN
ajst-16317	148	17	and	and	CCONJ
ajst-16317	148	18	calculates	calculate	VERB
ajst-16317	148	19	the	the	DET
ajst-16317	148	20	similarity	similarity	NOUN
ajst-16317	148	21	score	score	NOUN
ajst-16317	148	22	between	between	ADP
ajst-16317	148	23	each	each	DET
ajst-16317	148	24	sample	sample	NOUN
ajst-16317	148	25	and	and	CCONJ
ajst-16317	148	26	other	other	ADJ
ajst-16317	148	27	samples	sample	NOUN
ajst-16317	148	28	.	.	PUNCT
ajst-16317	149	1	specifically	specifically	ADV
ajst-16317	149	2	,	,	PUNCT
ajst-16317	149	3	for	for	ADP
ajst-16317	149	4	a	a	DET
ajst-16317	149	5	given	give	VERB
ajst-16317	149	6	pair	pair	NOUN
ajst-16317	149	7	of	of	ADP
ajst-16317	149	8	samples（𝑋	samples（𝑋	PROPN
ajst-16317	149	9	,	,	PUNCT
ajst-16317	149	10	𝑋	𝑋	PROPN
ajst-16317	149	11	,	,	PUNCT
ajst-16317	149	12	we	we	PRON
ajst-16317	149	13	can	can	AUX
ajst-16317	149	14	encode	encode	VERB
ajst-16317	149	15	them	they	PRON
ajst-16317	149	16	into	into	ADP
ajst-16317	149	17	feature	feature	NOUN
ajst-16317	149	18	vectors	vector	NOUN
ajst-16317	149	19	by𝑍	by𝑍	ADJ
ajst-16317	149	20	and𝑍	and𝑍	NOUN
ajst-16317	149	21	,	,	PUNCT
ajst-16317	149	22	and	and	CCONJ
ajst-16317	149	23	calculate	calculate	VERB
ajst-16317	149	24	the	the	DET
ajst-16317	149	25	cosine	cosine	NOUN
ajst-16317	149	26	similarity	similarity	NOUN
ajst-16317	149	27	score	score	NOUN
ajst-16317	149	28	𝑆	𝑆	PROPN
ajst-16317	149	29	between	between	ADP
ajst-16317	149	30	them	they	PRON
ajst-16317	149	31	to	to	PART
ajst-16317	149	32	measure	measure	VERB
ajst-16317	149	33	the	the	DET
ajst-16317	149	34	similarity	similarity	NOUN
ajst-16317	149	35	between	between	ADP
ajst-16317	149	36	them	they	PRON
ajst-16317	149	37	.	.	PUNCT
ajst-16317	150	1	the	the	DET
ajst-16317	150	2	cosine	cosine	NOUN
ajst-16317	150	3	similarity	similarity	NOUN
ajst-16317	150	4	score	score	NOUN
ajst-16317	150	5	can	can	AUX
ajst-16317	150	6	be	be	AUX
ajst-16317	150	7	expressed	express	VERB
ajst-16317	150	8	as	as	ADP
ajst-16317	150	9	:	:	PUNCT
ajst-16317	150	10	𝑆	𝑆	PROPN
ajst-16317	150	11	‖	‖	PROPN
ajst-16317	150	12	‖	‖	PROPN
ajst-16317	150	13	(	(	PUNCT
ajst-16317	150	14	in‖𝑍	in‖𝑍	PROPN
ajst-16317	150	15	‖	‖	PROPN
ajst-16317	150	16	and	and	CCONJ
ajst-16317	150	17	𝑍	𝑍	PROPN
ajst-16317	150	18	represent	represent	VERB
ajst-16317	150	19	the	the	DET
ajst-16317	150	20	norms	norm	NOUN
ajst-16317	150	21	of	of	ADP
ajst-16317	150	22	𝑍	𝑍	NOUN
ajst-16317	150	23	𝑎𝑛𝑑𝑍	𝑎𝑛𝑑𝑍	NOUN
ajst-16317	150	24	respectively	respectively	ADV
ajst-16317	150	25	.	.	PUNCT
ajst-16317	150	26	)	)	PUNCT
ajst-16317	151	1	these	these	DET
ajst-16317	151	2	similarity	similarity	NOUN
ajst-16317	151	3	scores	score	NOUN
ajst-16317	151	4	are	be	AUX
ajst-16317	151	5	then	then	ADV
ajst-16317	151	6	fed	feed	VERB
ajst-16317	151	7	into	into	ADP
ajst-16317	151	8	a	a	DET
ajst-16317	151	9	normalized	normalize	VERB
ajst-16317	151	10	temperature	temperature	NOUN
ajst-16317	151	11	-	-	PUNCT
ajst-16317	151	12	scaled	scale	VERB
ajst-16317	151	13	cross	cross	ADJ
ajst-16317	151	14	-	-	ADJ
ajst-16317	151	15	entropy	entropy	ADJ
ajst-16317	151	16	loss	loss	NOUN
ajst-16317	151	17	,	,	PUNCT
ajst-16317	151	18	which	which	PRON
ajst-16317	151	19	is	be	AUX
ajst-16317	151	20	defined	define	VERB
ajst-16317	151	21	as	as	SCONJ
ajst-16317	151	22	follows	follow	VERB
ajst-16317	151	23	:	:	PUNCT
ajst-16317	151	24	,	,	PUNCT
ajst-16317	151	25	2	2	NUM
ajst-16317	151	26	,	,	PUNCT
ajst-16317	151	27	,	,	PUNCT
ajst-16317	151	28	1	1	NUM
ajst-16317	151	29	1	1	NUM
ajst-16317	151	30	exp	exp	NOUN
ajst-16317	151	31	(	(	PUNCT
ajst-16317	151	32	)	)	PUNCT
ajst-16317	151	33	1	1	NUM
ajst-16317	151	34	log	log	NOUN
ajst-16317	151	35	exp	exp	NOUN
ajst-16317	151	36	(	(	PUNCT
ajst-16317	151	37	)	)	PUNCT
ajst-16317	151	38	exp	exp	NOUN
ajst-16317	151	39	(	(	PUNCT
ajst-16317	151	40	)	)	PUNCT
ajst-16317	152	1	i	i	PRON
ajst-16317	152	2	j	j	PROPN
ajst-16317	152	3	n	n	CCONJ
ajst-16317	152	4	n	n	CCONJ
ajst-16317	152	5	n	n	NOUN
ajst-16317	153	1	i	i	PRON
ajst-16317	153	2	j	j	INTJ
ajst-16317	154	1	i	i	PRON
ajst-16317	154	2	ji	ji	PROPN
ajst-16317	155	1	j	j	PROPN
ajst-16317	155	2	s	s	PROPN
ajst-16317	155	3	l	l	NOUN
ajst-16317	155	4	s	s	PART
ajst-16317	155	5	sn	sn	NOUN
ajst-16317	155	6			NOUN
ajst-16317	155	7			NOUN
ajst-16317	155	8			NOUN
ajst-16317	155	9			VERB
ajst-16317	155	10			PROPN
ajst-16317	155	11			NUM
ajst-16317	155	12			PROPN
ajst-16317	155	13			PROPN
ajst-16317	155	14			PROPN
ajst-16317	155	15			X
ajst-16317	155	16			X
ajst-16317	155	17	among	among	ADP
ajst-16317	155	18	them	they	PRON
ajst-16317	155	19	,	,	PUNCT
ajst-16317	155	20	n	n	PRON
ajst-16317	155	21	represents	represent	VERB
ajst-16317	155	22	the	the	DET
ajst-16317	155	23	batch	batch	NOUN
ajst-16317	155	24	size	size	NOUN
ajst-16317	155	25	,	,	PUNCT
ajst-16317	155	26	n	n	X
ajst-16317	155	27	is	be	AUX
ajst-16317	155	28	the	the	DET
ajst-16317	155	29	number	number	NOUN
ajst-16317	155	30	of	of	ADP
ajst-16317	155	31	adjacent	adjacent	ADJ
ajst-16317	155	32	samples	sample	NOUN
ajst-16317	155	33	for	for	ADP
ajst-16317	155	34	each	each	DET
ajst-16317	155	35	sample	sample	NOUN
ajst-16317	155	36	,	,	PUNCT
ajst-16317	155	37			PROPN
ajst-16317	155	38	is	be	AUX
ajst-16317	155	39	the	the	DET
ajst-16317	155	40	temperature	temperature	NOUN
ajst-16317	155	41	parameter	parameter	NOUN
ajst-16317	155	42	,	,	PUNCT
ajst-16317	155	43	for	for	ADP
ajst-16317	155	44	scaled	scale	VERB
ajst-16317	155	45	cosine	cosine	NOUN
ajst-16317	155	46	similarity	similarity	NOUN
ajst-16317	155	47	score	score	NOUN
ajst-16317	155	48	,	,	PUNCT
ajst-16317	155	49	,	,	PUNCT
ajst-16317	155	50	i	i	PRON
ajst-16317	155	51	j	j	PROPN
ajst-16317	155	52	ns	ns	NUM
ajst-16317	155	53			ADV
ajst-16317	155	54	represents	represent	VERB
ajst-16317	155	55	the	the	DET
ajst-16317	155	56	similarity	similarity	NOUN
ajst-16317	155	57	score	score	NOUN
ajst-16317	155	58	of	of	ADP
ajst-16317	155	59	the	the	DET
ajst-16317	155	60	positive	positive	ADJ
ajst-16317	155	61	sample	sample	NOUN
ajst-16317	155	62	to	to	ADP
ajst-16317	155	63	,	,	PUNCT
ajst-16317	155	64	)	)	PUNCT
ajst-16317	156	1	i	i	PRON
ajst-16317	156	2	i	i	PRON
ajst-16317	156	3	nx	nx	VERB
ajst-16317	156	4	x	x	SYM
ajst-16317	156	5			PROPN
ajst-16317	156	6	（	（	PUNCT
ajst-16317	156	7	.	.	PUNCT
ajst-16317	157	1	nt	not	PART
ajst-16317	157	2	-	-	PUNCT
ajst-16317	157	3	xent	xent	ADJ
ajst-16317	157	4	loss	loss	NOUN
ajst-16317	157	5	is	be	AUX
ajst-16317	157	6	an	an	DET
ajst-16317	157	7	effective	effective	ADJ
ajst-16317	157	8	contrastive	contrastive	ADJ
ajst-16317	157	9	learning	learning	NOUN
ajst-16317	157	10	loss	loss	NOUN
ajst-16317	157	11	function	function	NOUN
ajst-16317	157	12	that	that	PRON
ajst-16317	157	13	is	be	AUX
ajst-16317	157	14	widely	widely	ADV
ajst-16317	157	15	used	use	VERB
ajst-16317	157	16	when	when	SCONJ
ajst-16317	157	17	training	train	VERB
ajst-16317	157	18	large	large	ADJ
ajst-16317	157	19	deep	deep	ADJ
ajst-16317	157	20	learning	learning	NOUN
ajst-16317	157	21	models	model	NOUN
ajst-16317	157	22	.	.	PUNCT
ajst-16317	158	1	3.3.2	3.3.2	X
ajst-16317	158	2	.	.	X
ajst-16317	158	3	fine	fine	ADV
ajst-16317	158	4	-	-	PUNCT
ajst-16317	158	5	tuning	tune	VERB
ajst-16317	158	6	the	the	DET
ajst-16317	158	7	loss	loss	NOUN
ajst-16317	158	8	function	function	NOUN
ajst-16317	158	9	matchloss	matchloss	NOUN
ajst-16317	158	10	is	be	AUX
ajst-16317	158	11	a	a	DET
ajst-16317	158	12	loss	loss	NOUN
ajst-16317	158	13	function	function	NOUN
ajst-16317	158	14	used	use	VERB
ajst-16317	158	15	to	to	ADP
ajst-16317	158	16	fine	fine	ADJ
ajst-16317	158	17	-	-	PUNCT
ajst-16317	158	18	tune	tune	NOUN
ajst-16317	158	19	the	the	DET
ajst-16317	158	20	model	model	NOUN
ajst-16317	158	21	.	.	PUNCT
ajst-16317	159	1	its	its	PRON
ajst-16317	159	2	main	main	ADJ
ajst-16317	159	3	goal	goal	NOUN
ajst-16317	159	4	is	be	AUX
ajst-16317	159	5	to	to	PART
ajst-16317	159	6	make	make	VERB
ajst-16317	159	7	the	the	DET
ajst-16317	159	8	features	feature	NOUN
ajst-16317	159	9	of	of	ADP
ajst-16317	159	10	images	image	NOUN
ajst-16317	159	11	and	and	CCONJ
ajst-16317	159	12	text	text	NOUN
ajst-16317	159	13	more	more	ADV
ajst-16317	159	14	similar	similar	ADJ
ajst-16317	159	15	in	in	ADP
ajst-16317	159	16	similarity	similarity	NOUN
ajst-16317	159	17	.	.	PUNCT
ajst-16317	160	1	matchloss	matchloss	PROPN
ajst-16317	160	2	is	be	AUX
ajst-16317	160	3	often	often	ADV
ajst-16317	160	4	used	use	VERB
ajst-16317	160	5	with	with	ADP
ajst-16317	160	6	contrastive	contrastive	ADJ
ajst-16317	160	7	learning	learning	NOUN
ajst-16317	160	8	loss	loss	NOUN
ajst-16317	160	9	.	.	PUNCT
ajst-16317	161	1	when	when	SCONJ
ajst-16317	161	2	using	use	VERB
ajst-16317	161	3	matchloss	matchloss	ADV
ajst-16317	161	4	,	,	PUNCT
ajst-16317	161	5	we	we	PRON
ajst-16317	161	6	first	first	ADV
ajst-16317	161	7	encode	encode	VERB
ajst-16317	161	8	the	the	DET
ajst-16317	161	9	image	image	NOUN
ajst-16317	161	10	and	and	CCONJ
ajst-16317	161	11	text	text	NOUN
ajst-16317	161	12	into	into	ADP
ajst-16317	161	13	feature	feature	NOUN
ajst-16317	161	14	vectors	vector	NOUN
ajst-16317	161	15	respectively	respectively	ADV
ajst-16317	161	16	,	,	PUNCT
ajst-16317	161	17	and	and	CCONJ
ajst-16317	161	18	then	then	ADV
ajst-16317	161	19	measure	measure	VERB
ajst-16317	161	20	the	the	DET
ajst-16317	161	21	similarity	similarity	NOUN
ajst-16317	161	22	between	between	ADP
ajst-16317	161	23	them	they	PRON
ajst-16317	161	24	by	by	ADP
ajst-16317	161	25	calculating	calculate	VERB
ajst-16317	161	26	the	the	DET
ajst-16317	161	27	cosine	cosine	NOUN
ajst-16317	161	28	similarity	similarity	NOUN
ajst-16317	161	29	score	score	NOUN
ajst-16317	161	30	between	between	ADP
ajst-16317	161	31	them	they	PRON
ajst-16317	161	32	.	.	PUNCT
ajst-16317	162	1	suppose	suppose	VERB
ajst-16317	162	2	we	we	PRON
ajst-16317	162	3	have	have	VERB
ajst-16317	162	4	a	a	DET
ajst-16317	162	5	positive	positive	ADJ
ajst-16317	162	6	sample	sample	NOUN
ajst-16317	162	7	pair	pair	NOUN
ajst-16317	162	8	,	,	PUNCT
ajst-16317	162	9	)	)	PUNCT
ajst-16317	162	10	i	i	PRON
ajst-16317	162	11	it（x	it（x	INTJ
ajst-16317	162	12	,	,	PUNCT
ajst-16317	162	13	where	where	SCONJ
ajst-16317	162	14	ix	ix	ADV
ajst-16317	162	15	represents	represent	VERB
ajst-16317	162	16	the	the	DET
ajst-16317	162	17	image	image	NOUN
ajst-16317	162	18	,	,	PUNCT
ajst-16317	162	19	it	it	PRON
ajst-16317	162	20	represents	represent	VERB
ajst-16317	162	21	the	the	DET
ajst-16317	162	22	corresponding	correspond	VERB
ajst-16317	162	23	text	text	NOUN
ajst-16317	162	24	.	.	PUNCT
ajst-16317	163	1	we	we	PRON
ajst-16317	163	2	can	can	AUX
ajst-16317	163	3	encode	encode	VERB
ajst-16317	163	4	them	they	PRON
ajst-16317	163	5	as	as	ADP
ajst-16317	163	6	feature	feature	NOUN
ajst-16317	163	7	vectors	vector	NOUN
ajst-16317	163	8	x	x	SYM
ajst-16317	164	1	iz	iz	INTJ
ajst-16317	164	2	and	and	CCONJ
ajst-16317	164	3	t	t	PROPN
ajst-16317	164	4	iz	iz	CCONJ
ajst-16317	164	5	respectively	respectively	ADV
ajst-16317	164	6	and	and	CCONJ
ajst-16317	164	7	calculate	calculate	VERB
ajst-16317	164	8	the	the	DET
ajst-16317	164	9	cosine	cosine	NOUN
ajst-16317	164	10	similarity	similarity	NOUN
ajst-16317	164	11	is	be	AUX
ajst-16317	164	12	between	between	ADP
ajst-16317	164	13	them	they	PRON
ajst-16317	164	14	as	as	SCONJ
ajst-16317	164	15	follows	follow	VERB
ajst-16317	164	16	:	:	PUNCT
ajst-16317	165	1	2	2	NUM
ajst-16317	165	2	2	2	NUM
ajst-16317	165	3	x	x	SYM
ajst-16317	165	4	t	t	NOUN
ajst-16317	166	1	i	i	PRON
ajst-16317	166	2	j	j	INTJ
ajst-16317	167	1	i	i	PRON
ajst-16317	167	2	x	x	PROPN
ajst-16317	168	1	t	t	NOUN
ajst-16317	169	1	i	i	PRON
ajst-16317	169	2	j	j	PROPN
ajst-16317	170	1	z	z	PROPN
ajst-16317	170	2	z	z	PROPN
ajst-16317	170	3	s	s	PROPN
ajst-16317	170	4	z	z	NOUN
ajst-16317	170	5	z	z	NOUN
ajst-16317	170	6			NUM
ajst-16317	170	7			NUM
ajst-16317	170	8	,	,	PUNCT
ajst-16317	170	9	where	where	SCONJ
ajst-16317	170	10			PRON
ajst-16317	170	11	represents	represent	VERB
ajst-16317	170	12	the	the	DET
ajst-16317	170	13	dot	dot	NOUN
ajst-16317	170	14	product	product	NOUN
ajst-16317	170	15	operation	operation	NOUN
ajst-16317	170	16	,	,	PUNCT
ajst-16317	170	17	represent	represent	VERB
ajst-16317	170	18	the	the	DET
ajst-16317	170	19	norms	norm	NOUN
ajst-16317	170	20	of	of	ADP
ajst-16317	170	21	𝑍	𝑍	NOUN
ajst-16317	170	22	𝑎𝑛𝑑𝑍	𝑎𝑛𝑑𝑍	NOUN
ajst-16317	170	23	respectively	respectively	ADV
ajst-16317	170	24	.	.	PUNCT
ajst-16317	171	1	next	next	ADV
ajst-16317	171	2	,	,	PUNCT
ajst-16317	171	3	we	we	PRON
ajst-16317	171	4	define	define	VERB
ajst-16317	171	5	matchloss	matchloss	ADV
ajst-16317	171	6	as	as	ADP
ajst-16317	171	7	the	the	DET
ajst-16317	171	8	average	average	NOUN
ajst-16317	171	9	of	of	ADP
ajst-16317	171	10	the	the	DET
ajst-16317	171	11	cosine	cosine	NOUN
ajst-16317	171	12	similarity	similarity	NOUN
ajst-16317	171	13	scores	score	NOUN
ajst-16317	171	14	of	of	ADP
ajst-16317	171	15	all	all	DET
ajst-16317	171	16	positive	positive	ADJ
ajst-16317	171	17	samples	sample	NOUN
ajst-16317	171	18	:	:	PUNCT
ajst-16317	171	19	1	1	NUM
ajst-16317	171	20	1	1	NUM
ajst-16317	171	21	n	n	PRON
ajst-16317	171	22	match	match	VERB
ajst-16317	172	1	i	i	PRON
ajst-16317	173	1	i	i	PRON
ajst-16317	173	2	l	l	NOUN
ajst-16317	173	3	s	s	VERB
ajst-16317	173	4	n	n	PRON
ajst-16317	174	1			NUM
ajst-16317	174	2			PROPN
ajst-16317	174	3			NOUN
ajst-16317	174	4			X
ajst-16317	174	5	by	by	ADP
ajst-16317	174	6	minimizing	minimize	VERB
ajst-16317	174	7	matchloss	matchloss	ADP
ajst-16317	174	8	,	,	PUNCT
ajst-16317	174	9	the	the	DET
ajst-16317	174	10	model	model	NOUN
ajst-16317	174	11	can	can	AUX
ajst-16317	174	12	learn	learn	VERB
ajst-16317	174	13	more	more	ADJ
ajst-16317	174	14	matching	matching	NOUN
ajst-16317	174	15	image	image	NOUN
ajst-16317	174	16	and	and	CCONJ
ajst-16317	174	17	text	text	NOUN
ajst-16317	174	18	feature	feature	NOUN
ajst-16317	174	19	representations	representation	NOUN
ajst-16317	174	20	,	,	PUNCT
ajst-16317	174	21	thereby	thereby	ADV
ajst-16317	174	22	improving	improve	VERB
ajst-16317	174	23	the	the	DET
ajst-16317	174	24	performance	performance	NOUN
ajst-16317	174	25	of	of	ADP
ajst-16317	174	26	the	the	DET
ajst-16317	174	27	model	model	NOUN
ajst-16317	174	28	.	.	PUNCT
ajst-16317	175	1	4	4	X
ajst-16317	175	2	.	.	X
ajst-16317	175	3	experimental	experimental	ADJ
ajst-16317	175	4	results	result	NOUN
ajst-16317	175	5	and	and	CCONJ
ajst-16317	175	6	analysis	analysis	NOUN
ajst-16317	175	7	table	table	NOUN
ajst-16317	175	8	1	1	NUM
ajst-16317	175	9	demonstrates	demonstrate	VERB
ajst-16317	175	10	the	the	DET
ajst-16317	175	11	significant	significant	ADJ
ajst-16317	175	12	performance	performance	NOUN
ajst-16317	175	13	strides	stride	NOUN
ajst-16317	175	14	accomplished	accomplish	VERB
ajst-16317	175	15	by	by	ADP
ajst-16317	175	16	blip	blip	NOUN
ajst-16317	175	17	in	in	ADP
ajst-16317	175	18	contrast	contrast	NOUN
ajst-16317	175	19	to	to	ADP
ajst-16317	175	20	established	establish	VERB
ajst-16317	175	21	methodologies	methodology	NOUN
ajst-16317	175	22	.	.	PUNCT
ajst-16317	176	1	leveraging	leverage	VERB
ajst-16317	176	2	identical	identical	ADJ
ajst-16317	176	3	14	14	NUM
ajst-16317	176	4	m	m	NOUN
ajst-16317	176	5	pre	pre	ADJ
ajst-16317	176	6	-	-	ADJ
ajst-16317	176	7	training	training	ADJ
ajst-16317	176	8	images	image	NOUN
ajst-16317	176	9	,	,	PUNCT
ajst-16317	176	10	blip	blip	NOUN
ajst-16317	176	11	surpasses	surpass	VERB
ajst-16317	176	12	the	the	DET
ajst-16317	176	13	prior	prior	ADJ
ajst-16317	176	14	leading	lead	VERB
ajst-16317	176	15	model	model	NOUN
ajst-16317	176	16	albef	albef	NOUN
ajst-16317	176	17	by	by	ADP
ajst-16317	176	18	+2.7	+2.7	PROPN
ajst-16317	176	19	%	%	NOUN
ajst-16317	176	20	in	in	ADP
ajst-16317	176	21	average	average	ADJ
ajst-16317	176	22	recall@1	recall@1	NOUN
ajst-16317	176	23	on	on	ADP
ajst-16317	176	24	coco	coco	PROPN
ajst-16317	176	25	.	.	PUNCT
ajst-16317	177	1	additionally	additionally	ADV
ajst-16317	177	2	,	,	PUNCT
ajst-16317	177	3	our	our	PRON
ajst-16317	177	4	zeroshot	zeroshot	NOUN
ajst-16317	177	5	retrieval	retrieval	NOUN
ajst-16317	177	6	experiment	experiment	NOUN
ajst-16317	177	7	involves	involve	VERB
ajst-16317	177	8	transferring	transfer	VERB
ajst-16317	177	9	the	the	DET
ajst-16317	177	10	model	model	NOUN
ajst-16317	177	11	fine	fine	ADV
ajst-16317	177	12	-	-	PUNCT
ajst-16317	177	13	tuned	tune	VERB
ajst-16317	177	14	on	on	ADP
ajst-16317	177	15	coco	coco	PROPN
ajst-16317	177	16	directly	directly	ADV
ajst-16317	177	17	to	to	ADP
ajst-16317	177	18	flickr30k	flickr30k	PROPN
ajst-16317	177	19	,	,	PUNCT
ajst-16317	177	20	yielding	yield	VERB
ajst-16317	177	21	compelling	compelling	ADJ
ajst-16317	177	22	outcomes	outcome	NOUN
ajst-16317	177	23	showcased	showcase	VERB
ajst-16317	177	24	in	in	ADP
ajst-16317	177	25	table	table	NOUN
ajst-16317	177	26	2	2	NUM
ajst-16317	177	27	.	.	PUNCT
ajst-16317	177	28	notably	notably	ADV
ajst-16317	177	29	,	,	PUNCT
ajst-16317	177	30	blip	blip	NOUN
ajst-16317	177	31	exhibits	exhibit	VERB
ajst-16317	177	32	a	a	DET
ajst-16317	177	33	substantial	substantial	ADJ
ajst-16317	177	34	performance	performance	NOUN
ajst-16317	177	35	advantage	advantage	NOUN
ajst-16317	177	36	over	over	ADP
ajst-16317	177	37	existing	exist	VERB
ajst-16317	177	38	methods	method	NOUN
ajst-16317	177	39	in	in	ADP
ajst-16317	177	40	this	this	DET
ajst-16317	177	41	domain	domain	NOUN
ajst-16317	177	42	as	as	ADV
ajst-16317	177	43	well	well	ADV
ajst-16317	177	44	.	.	PUNCT
ajst-16317	178	1	table	table	NOUN
ajst-16317	178	2	1	1	NUM
ajst-16317	178	3	.	.	PUNCT
ajst-16317	178	4	comparison	comparison	NOUN
ajst-16317	178	5	with	with	ADP
ajst-16317	178	6	state	state	NOUN
ajst-16317	178	7	-	-	PUNCT
ajst-16317	178	8	of	of	ADP
ajst-16317	178	9	-	-	PUNCT
ajst-16317	178	10	the	the	DET
ajst-16317	178	11	-	-	PUNCT
ajst-16317	178	12	art	art	NOUN
ajst-16317	178	13	image	image	NOUN
ajst-16317	178	14	-	-	PUNCT
ajst-16317	178	15	text	text	NOUN
ajst-16317	178	16	retrieval	retrieval	NOUN
ajst-16317	178	17	methods	method	NOUN
ajst-16317	178	18	,	,	PUNCT
ajst-16317	178	19	finetuned	finetune	VERB
ajst-16317	178	20	on	on	ADP
ajst-16317	178	21	coco	coco	PROPN
ajst-16317	178	22	and	and	CCONJ
ajst-16317	178	23	flickr30k	flickr30k	ADJ
ajst-16317	178	24	datasets	dataset	NOUN
ajst-16317	178	25	.	.	PUNCT
ajst-16317	179	1	method	method	PROPN
ajst-16317	179	2	pretrain	pretrain	NOUN
ajst-16317	179	3	#	#	SYM
ajst-16317	179	4	images	image	NOUN
ajst-16317	179	5	coco	coco	NOUN
ajst-16317	179	6	(	(	PUNCT
ajst-16317	179	7	5k	5k	NUM
ajst-16317	179	8	test	test	NOUN
ajst-16317	179	9	set	set	NOUN
ajst-16317	179	10	)	)	PUNCT
ajst-16317	179	11	flickr30k	flickr30k	NOUN
ajst-16317	179	12	(	(	PUNCT
ajst-16317	179	13	1k	1k	NUM
ajst-16317	179	14	test	test	NOUN
ajst-16317	179	15	set	set	NOUN
ajst-16317	179	16	)	)	PUNCT
ajst-16317	179	17	tr	tr	VERB
ajst-16317	179	18	ir	ir	PROPN
ajst-16317	179	19	tr	tr	VERB
ajst-16317	179	20	ir	ir	PROPN
ajst-16317	179	21	r@1	r@1	PROPN
ajst-16317	179	22	r@5	r@5	PROPN
ajst-16317	179	23	r@10	r@10	PUNCT
ajst-16317	179	24	r@1	r@1	PROPN
ajst-16317	179	25	r@5	r@5	PROPN
ajst-16317	179	26	r@10	r@10	NOUN
ajst-16317	179	27	r@1	r@1	PROPN
ajst-16317	179	28	r@5	r@5	PROPN
ajst-16317	179	29	r@10	r@10	NOUN
ajst-16317	179	30	r@1	r@1	PROPN
ajst-16317	179	31	r@5	r@5	PROPN
ajst-16317	179	32	r@10	r@10	NUM
ajst-16317	179	33	uniter	uniter	NOUN
ajst-16317	179	34	4	4	NUM
ajst-16317	179	35	m	m	NOUN
ajst-16317	179	36	65.7	65.7	NUM
ajst-16317	179	37	88.6	88.6	NUM
ajst-16317	179	38	93.8	93.8	NUM
ajst-16317	179	39	52.9	52.9	NUM
ajst-16317	179	40	79.9	79.9	NUM
ajst-16317	179	41	88.0	88.0	NUM
ajst-16317	179	42	87.3	87.3	NUM
ajst-16317	179	43	98.0	98.0	NUM
ajst-16317	179	44	99.2	99.2	NUM
ajst-16317	179	45	75.6	75.6	NUM
ajst-16317	179	46	94.1	94.1	NUM
ajst-16317	179	47	96.8	96.8	NUM
ajst-16317	179	48	villa	villa	NOUN
ajst-16317	179	49	4	4	NUM
ajst-16317	179	50	m	m	NOUN
ajst-16317	179	51	87.9	87.9	NUM
ajst-16317	179	52	97.5	97.5	NUM
ajst-16317	179	53	98.8	98.8	NUM
ajst-16317	179	54	76.3	76.3	NUM
ajst-16317	179	55	94.2	94.2	NUM
ajst-16317	179	56	96.8	96.8	NUM
ajst-16317	179	57	oscar	oscar	NOUN
ajst-16317	179	58	4	4	NUM
ajst-16317	179	59	m	m	NOUN
ajst-16317	179	60	70.0	70.0	NUM
ajst-16317	179	61	91.1	91.1	NUM
ajst-16317	179	62	95.5	95.5	NUM
ajst-16317	179	63	54.0	54.0	NUM
ajst-16317	179	64	80.8	80.8	NUM
ajst-16317	179	65	88.5	88.5	NUM
ajst-16317	179	66	unimo	unimo	ADJ
ajst-16317	179	67	5.7	5.7	NUM
ajst-16317	179	68	m	m	NOUN
ajst-16317	179	69	89.4	89.4	NUM
ajst-16317	179	70	98.9	98.9	NUM
ajst-16317	179	71	99.8	99.8	NUM
ajst-16317	179	72	78.0	78.0	NUM
ajst-16317	179	73	94.2	94.2	NUM
ajst-16317	179	74	97.1	97.1	NUM
ajst-16317	179	75	align	align	NOUN
ajst-16317	179	76	1.8b	1.8b	NUM
ajst-16317	179	77	77.0	77.0	NUM
ajst-16317	179	78	93.5	93.5	NUM
ajst-16317	179	79	96.9	96.9	NUM
ajst-16317	179	80	59.9	59.9	NUM
ajst-16317	179	81	83.3	83.3	NUM
ajst-16317	179	82	89.8	89.8	NUM
ajst-16317	179	83	95.3	95.3	NUM
ajst-16317	179	84	99.8	99.8	NUM
ajst-16317	179	85	100.0	100.0	NUM
ajst-16317	179	86	84.9	84.9	NUM
ajst-16317	179	87	97.4	97.4	NUM
ajst-16317	179	88	98.6	98.6	NUM
ajst-16317	179	89	albef	albef	ADJ
ajst-16317	179	90	14	14	NUM
ajst-16317	179	91	m	m	PROPN
ajst-16317	179	92	77.6	77.6	NUM
ajst-16317	179	93	94.3	94.3	NUM
ajst-16317	179	94	97.2	97.2	NUM
ajst-16317	179	95	60.7	60.7	NUM
ajst-16317	179	96	84.3	84.3	NUM
ajst-16317	179	97	90.5	90.5	NUM
ajst-16317	179	98	95.9	95.9	NUM
ajst-16317	179	99	99.8	99.8	NUM
ajst-16317	179	100	100.0	100.0	NUM
ajst-16317	179	101	85.6	85.6	NUM
ajst-16317	179	102	97.5	97.5	NUM
ajst-16317	179	103	98.9	98.9	NUM
ajst-16317	179	104	blipvit	blipvit	NOUN
ajst-16317	179	105	-	-	PUNCT
ajst-16317	179	106	l	l	NOUN
ajst-16317	179	107	129	129	NUM
ajst-16317	179	108	m	m	NOUN
ajst-16317	179	109	82.4	82.4	NUM
ajst-16317	179	110	95.4	95.4	NUM
ajst-16317	179	111	97.9	97.9	NUM
ajst-16317	179	112	65.1	65.1	NUM
ajst-16317	179	113	86.3	86.3	NUM
ajst-16317	179	114	91.8	91.8	NUM
ajst-16317	179	115	97.4	97.4	NUM
ajst-16317	179	116	99.8	99.8	NUM
ajst-16317	179	117	99.9	99.9	NUM
ajst-16317	179	118	87.6	87.6	NUM
ajst-16317	179	119	97.7	97.7	NUM
ajst-16317	179	120	99.0	99.0	NUM
ajst-16317	179	121	85	85	NUM
ajst-16317	179	122	table	table	NOUN
ajst-16317	179	123	2	2	NUM
ajst-16317	179	124	.	.	NUM
ajst-16317	179	125	zero	zero	NUM
ajst-16317	179	126	-	-	PUNCT
ajst-16317	179	127	shot	shot	NOUN
ajst-16317	179	128	image	image	NOUN
ajst-16317	179	129	-	-	PUNCT
ajst-16317	179	130	text	text	NOUN
ajst-16317	179	131	retrieval	retrieval	NOUN
ajst-16317	179	132	results	result	NOUN
ajst-16317	179	133	on	on	ADP
ajst-16317	179	134	flickr30k	flickr30k	PROPN
ajst-16317	179	135	.	.	PROPN
ajst-16317	179	136	method	method	PROPN
ajst-16317	179	137	pre	pre	ADJ
ajst-16317	179	138	-	-	ADJ
ajst-16317	179	139	train	train	ADJ
ajst-16317	179	140	#	#	NOUN
ajst-16317	179	141	images	image	NOUN
ajst-16317	179	142	flickr30k	flickr30k	NOUN
ajst-16317	179	143	(	(	PUNCT
ajst-16317	179	144	1k	1k	NUM
ajst-16317	179	145	test	test	NOUN
ajst-16317	179	146	set	set	NOUN
ajst-16317	179	147	)	)	PUNCT
ajst-16317	179	148	tr	tr	VERB
ajst-16317	179	149	ir	ir	PROPN
ajst-16317	179	150	r@1	r@1	PROPN
ajst-16317	179	151	r@5	r@5	PROPN
ajst-16317	179	152	r@10	r@10	PUNCT
ajst-16317	179	153	r@1	r@1	PROPN
ajst-16317	179	154	r@5	r@5	PROPN
ajst-16317	179	155	r@10	r@10	PUNCT
ajst-16317	179	156	clip	clip	NOUN
ajst-16317	179	157	400	400	NUM
ajst-16317	179	158	m	m	NOUN
ajst-16317	179	159	88.0	88.0	NUM
ajst-16317	179	160	98.7	98.7	NUM
ajst-16317	179	161	99.4	99.4	NUM
ajst-16317	179	162	68.7	68.7	NUM
ajst-16317	179	163	90.6	90.6	NUM
ajst-16317	179	164	95.2	95.2	NUM
ajst-16317	179	165	align	align	NOUN
ajst-16317	179	166	1.8b	1.8b	NUM
ajst-16317	179	167	88.6	88.6	NUM
ajst-16317	179	168	98.7	98.7	NUM
ajst-16317	179	169	99.7	99.7	NUM
ajst-16317	179	170	75.7	75.7	NUM
ajst-16317	179	171	93.8	93.8	NUM
ajst-16317	179	172	96.8	96.8	NUM
ajst-16317	179	173	albef	albef	ADJ
ajst-16317	179	174	14	14	NUM
ajst-16317	179	175	m	m	NOUN
ajst-16317	179	176	94.1	94.1	NUM
ajst-16317	179	177	99.5	99.5	NUM
ajst-16317	179	178	99.7	99.7	NUM
ajst-16317	179	179	82.8	82.8	NUM
ajst-16317	179	180	96.3	96.3	NUM
ajst-16317	179	181	98.1	98.1	NUM
ajst-16317	179	182	blipvit	blipvit	ADJ
ajst-16317	179	183	-	-	PUNCT
ajst-16317	179	184	l	l	NOUN
ajst-16317	179	185	129	129	NUM
ajst-16317	179	186	m	m	NOUN
ajst-16317	179	187	96.7	96.7	NUM
ajst-16317	179	188	100.0	100.0	NUM
ajst-16317	179	189	100.0	100.0	NUM
ajst-16317	179	190	86.7	86.7	NUM
ajst-16317	179	191	97.3	97.3	NUM
ajst-16317	179	192	98.7	98.7	NUM
ajst-16317	179	193	after	after	ADP
ajst-16317	179	194	completing	complete	VERB
ajst-16317	179	195	the	the	DET
ajst-16317	179	196	training	training	NOUN
ajst-16317	179	197	step	step	NOUN
ajst-16317	179	198	,	,	PUNCT
ajst-16317	179	199	we	we	PRON
ajst-16317	179	200	perform	perform	VERB
ajst-16317	179	201	performance	performance	NOUN
ajst-16317	179	202	testing	testing	NOUN
ajst-16317	179	203	on	on	ADP
ajst-16317	179	204	the	the	DET
ajst-16317	179	205	prediction	prediction	NOUN
ajst-16317	179	206	results	result	NOUN
ajst-16317	179	207	.	.	PUNCT
ajst-16317	180	1	it	it	PRON
ajst-16317	180	2	starts	start	VERB
ajst-16317	180	3	and	and	CCONJ
ajst-16317	180	4	ends	end	VERB
ajst-16317	180	5	with	with	ADP
ajst-16317	180	6	image	image	NOUN
ajst-16317	180	7	indexing	indexing	NOUN
ajst-16317	180	8	accelerated	accelerate	VERB
ajst-16317	180	9	by	by	ADP
ajst-16317	180	10	multiple	multiple	ADJ
ajst-16317	180	11	gpus	gpu	NOUN
ajst-16317	180	12	.	.	PUNCT
ajst-16317	181	1	on	on	ADP
ajst-16317	181	2	a100	a100	PROPN
ajst-16317	181	3	80	80	NUM
ajst-16317	181	4	g	g	PROPN
ajst-16317	181	5	gpu	gpu	PROPN
ajst-16317	181	6	,	,	PUNCT
ajst-16317	181	7	every	every	DET
ajst-16317	181	8	10	10	NUM
ajst-16317	181	9	image	image	NOUN
ajst-16317	181	10	-	-	PUNCT
ajst-16317	181	11	context	context	NOUN
ajst-16317	181	12	pairs	pair	NOUN
ajst-16317	181	13	takes	take	VERB
ajst-16317	181	14	3.6	3.6	NUM
ajst-16317	181	15	seconds	second	NOUN
ajst-16317	181	16	.	.	PUNCT
ajst-16317	182	1	the	the	DET
ajst-16317	182	2	test	test	NOUN
ajst-16317	182	3	process	process	NOUN
ajst-16317	182	4	and	and	CCONJ
ajst-16317	182	5	results	result	NOUN
ajst-16317	182	6	are	be	AUX
ajst-16317	182	7	as	as	SCONJ
ajst-16317	182	8	follows	follow	VERB
ajst-16317	182	9	:	:	PUNCT
ajst-16317	182	10	input	input	NOUN
ajst-16317	182	11	context1	context1	PROPN
ajst-16317	182	12	:	:	PUNCT
ajst-16317	182	13	"	"	PUNCT
ajst-16317	182	14	m	m	PROPN
ajst-16317	182	15	&	&	CCONJ
ajst-16317	182	16	d	d	PROPN
ajst-16317	182	17	simple	simple	ADJ
ajst-16317	182	18	modern	modern	ADJ
ajst-16317	182	19	light	light	ADJ
ajst-16317	182	20	luxury	luxury	NOUN
ajst-16317	182	21	comfort	comfort	PROPN
ajst-16317	182	22	good	good	ADJ
ajst-16317	182	23	quality	quality	NOUN
ajst-16317	182	24	living	living	NOUN
ajst-16317	182	25	room	room	NOUN
ajst-16317	182	26	with	with	ADP
ajst-16317	182	27	a	a	DET
ajst-16317	182	28	double	double	ADJ
ajst-16317	182	29	motor	motor	NOUN
ajst-16317	182	30	lounge	lounge	NOUN
ajst-16317	182	31	chair	chair	NOUN
ajst-16317	182	32	sofa	sofa	NOUN
ajst-16317	182	33	te04	te04	PROPN
ajst-16317	182	34	"	"	PUNCT
ajst-16317	182	35	.	.	PUNCT
ajst-16317	183	1	output	output	PROPN
ajst-16317	183	2	context1	context1	PROPN
ajst-16317	183	3	:	:	PUNCT
ajst-16317	183	4	good	good	ADJ
ajst-16317	183	5	quality	quality	NOUN
ajst-16317	183	6	living	living	NOUN
ajst-16317	183	7	room	room	NOUN
ajst-16317	183	8	with	with	ADP
ajst-16317	183	9	a	a	DET
ajst-16317	183	10	double	double	ADJ
ajst-16317	183	11	motor	motor	NOUN
ajst-16317	183	12	lounge	lounge	NOUN
ajst-16317	183	13	chair	chair	NOUN
ajst-16317	183	14	sofa	sofa	NOUN
ajst-16317	183	15	as	as	SCONJ
ajst-16317	183	16	shown	show	VERB
ajst-16317	183	17	in	in	ADP
ajst-16317	183	18	figure	figure	NOUN
ajst-16317	183	19	3	3	NUM
ajst-16317	183	20	.	.	PUNCT
ajst-16317	183	21	figure	figure	NOUN
ajst-16317	183	22	3	3	NUM
ajst-16317	183	23	.	.	PUNCT
ajst-16317	183	24	good	good	ADJ
ajst-16317	183	25	quality	quality	NOUN
ajst-16317	183	26	living	living	NOUN
ajst-16317	183	27	room	room	NOUN
ajst-16317	183	28	with	with	ADP
ajst-16317	183	29	a	a	DET
ajst-16317	183	30	double	double	ADJ
ajst-16317	183	31	motor	motor	NOUN
ajst-16317	183	32	lounge	lounge	NOUN
ajst-16317	183	33	chair	chair	NOUN
ajst-16317	183	34	sofa	sofa	NOUN
ajst-16317	183	35	input	input	NOUN
ajst-16317	183	36	context2	context2	NOUN
ajst-16317	183	37	:	:	PUNCT
ajst-16317	183	38	"	"	PUNCT
ajst-16317	183	39	er	er	INTJ
ajst-16317	183	40	tong	tong	PROPN
ajst-16317	183	41	hua	hua	PROPN
ajst-16317	183	42	xing	xing	PROPN
ajst-16317	183	43	che	che	PROPN
ajst-16317	183	44	fang	fang	PROPN
ajst-16317	183	45	ce	ce	PROPN
ajst-16317	183	46	fan	fan	PROPN
ajst-16317	183	47	niu	niu	PROPN
ajst-16317	183	48	niu	niu	PROPN
ajst-16317	183	49	che	che	PROPN
ajst-16317	183	50	1	1	NUM
ajst-16317	183	51	-	-	SYM
ajst-16317	183	52	3	3	NUM
ajst-16317	183	53	sui	sui	NOUN
ajst-16317	183	54	bao	bao	PROPN
ajst-16317	183	55	bao	bao	PROPN
ajst-16317	183	56	wan	wan	PROPN
ajst-16317	183	57	ju	ju	PROPN
ajst-16317	183	58	che	che	PROPN
ajst-16317	183	59	yin	yin	PROPN
ajst-16317	183	60	le	le	PROPN
ajst-16317	183	61	ke	ke	PROPN
ajst-16317	183	62	zuo	zuo	PROPN
ajst-16317	183	63	ke	ke	PROPN
ajst-16317	183	64	qi	qi	PROPN
ajst-16317	183	65	si	si	PROPN
ajst-16317	183	66	lun	lun	PROPN
ajst-16317	183	67	lium	lium	PROPN
ajst-16317	183	68	che	che	PROPN
ajst-16317	183	69	"	"	PUNCT
ajst-16317	183	70	.	.	PUNCT
ajst-16317	184	1	output	output	NOUN
ajst-16317	184	2	context2	context2	PROPN
ajst-16317	184	3	:	:	PUNCT
ajst-16317	184	4	er	er	INTJ
ajst-16317	184	5	tong	tong	PROPN
ajst-16317	184	6	hua	hua	PROPN
ajst-16317	184	7	xing	xing	PROPN
ajst-16317	184	8	che	che	PROPN
ajst-16317	184	9	fang	fang	PROPN
ajst-16317	184	10	ce	ce	PROPN
ajst-16317	184	11	fan	fan	PROPN
ajst-16317	184	12	niu	niu	PROPN
ajst-16317	184	13	niu	niu	PROPN
ajst-16317	184	14	che	che	PROPN
ajst-16317	184	15	as	as	SCONJ
ajst-16317	184	16	shown	show	VERB
ajst-16317	184	17	in	in	ADP
ajst-16317	184	18	figure	figure	NOUN
ajst-16317	184	19	4	4	NUM
ajst-16317	184	20	figure	figure	NOUN
ajst-16317	184	21	4	4	NUM
ajst-16317	184	22	.	.	PUNCT
ajst-16317	185	1	er	er	INTJ
ajst-16317	185	2	tong	tong	PROPN
ajst-16317	185	3	hua	hua	PROPN
ajst-16317	185	4	xing	xing	PROPN
ajst-16317	185	5	che	che	PROPN
ajst-16317	185	6	fang	fang	PROPN
ajst-16317	185	7	ce	ce	PROPN
ajst-16317	185	8	fan	fan	PROPN
ajst-16317	185	9	niu	niu	PROPN
ajst-16317	185	10	niu	niu	PROPN
ajst-16317	185	11	che	che	PROPN
ajst-16317	185	12	input	input	NOUN
ajst-16317	185	13	context3:"feiyangg	context3:"feiyangg	PROPN
ajst-16317	185	14	/	/	SYM
ajst-16317	185	15	lp	lp	PROPN
ajst-16317	185	16	paragraph	paragraph	NOUN
ajst-16317	185	17	style	style	NOUN
ajst-16317	185	18	electric	electric	PROPN
ajst-16317	185	19	guitar	guitar	NOUN
ajst-16317	185	20	tiger	tiger	NOUN
ajst-16317	185	21	veneer	veneer	NOUN
ajst-16317	185	22	factory	factory	NOUN
ajst-16317	185	23	direct	direct	ADJ
ajst-16317	185	24	color	color	NOUN
ajst-16317	185	25	can	can	AUX
ajst-16317	185	26	be	be	AUX
ajst-16317	185	27	customized	customize	VERB
ajst-16317	185	28	"	"	PUNCT
ajst-16317	185	29	output	output	NOUN
ajst-16317	185	30	context3	context3	ADV
ajst-16317	185	31	:	:	PUNCT
ajst-16317	185	32	feiyangg	feiyangg	ADJ
ajst-16317	185	33	/	/	SYM
ajst-16317	185	34	lp	lp	ADJ
ajst-16317	185	35	paragraph	paragraph	NOUN
ajst-16317	185	36	style	style	NOUN
ajst-16317	185	37	electric	electric	PROPN
ajst-16317	185	38	guitar	guitar	NOUN
ajst-16317	185	39	tiger	tiger	NOUN
ajst-16317	185	40	as	as	SCONJ
ajst-16317	185	41	shown	show	VERB
ajst-16317	185	42	in	in	ADP
ajst-16317	185	43	figure	figure	NOUN
ajst-16317	185	44	5	5	NUM
ajst-16317	185	45	:	:	PUNCT
ajst-16317	185	46	figure	figure	NOUN
ajst-16317	185	47	5	5	NUM
ajst-16317	185	48	.	.	PUNCT
ajst-16317	185	49	feiyangg	feiyangg	ADJ
ajst-16317	185	50	/	/	SYM
ajst-16317	185	51	lp	lp	PROPN
ajst-16317	185	52	paragraph	paragraph	NOUN
ajst-16317	185	53	style	style	NOUN
ajst-16317	185	54	electric	electric	PROPN
ajst-16317	185	55	guitar	guitar	NOUN
ajst-16317	185	56	tiger	tiger	NOUN
ajst-16317	185	57	5	5	NUM
ajst-16317	185	58	.	.	PUNCT
ajst-16317	185	59	conclusion	conclusion	NOUN
ajst-16317	185	60	in	in	ADP
ajst-16317	185	61	order	order	NOUN
ajst-16317	185	62	to	to	PART
ajst-16317	185	63	meet	meet	VERB
ajst-16317	185	64	the	the	DET
ajst-16317	185	65	actual	actual	ADJ
ajst-16317	185	66	needs	need	NOUN
ajst-16317	185	67	of	of	ADP
ajst-16317	185	68	existing	exist	VERB
ajst-16317	185	69	engine	engine	NOUN
ajst-16317	185	70	searches	search	NOUN
ajst-16317	185	71	to	to	PART
ajst-16317	185	72	improve	improve	VERB
ajst-16317	185	73	search	search	NOUN
ajst-16317	185	74	speed	speed	NOUN
ajst-16317	185	75	and	and	CCONJ
ajst-16317	185	76	search	search	NOUN
ajst-16317	185	77	accuracy	accuracy	NOUN
ajst-16317	185	78	,	,	PUNCT
ajst-16317	185	79	this	this	DET
ajst-16317	185	80	article	article	NOUN
ajst-16317	185	81	proposes	propose	VERB
ajst-16317	185	82	an	an	DET
ajst-16317	185	83	improved	improved	ADJ
ajst-16317	185	84	method	method	NOUN
ajst-16317	185	85	based	base	VERB
ajst-16317	185	86	on	on	ADP
ajst-16317	185	87	the	the	DET
ajst-16317	185	88	blip	blip	ADJ
ajst-16317	185	89	algorithm	algorithm	NOUN
ajst-16317	185	90	.	.	PUNCT
ajst-16317	186	1	we	we	PRON
ajst-16317	186	2	migrated	migrate	VERB
ajst-16317	186	3	the	the	DET
ajst-16317	186	4	image	image	NOUN
ajst-16317	186	5	and	and	CCONJ
ajst-16317	186	6	text	text	NOUN
ajst-16317	186	7	retrieval	retrieval	NOUN
ajst-16317	186	8	strategy	strategy	NOUN
ajst-16317	186	9	of	of	ADP
ajst-16317	186	10	the	the	DET
ajst-16317	186	11	blip	blip	ADJ
ajst-16317	186	12	algorithm	algorithm	NOUN
ajst-16317	186	13	from	from	ADP
ajst-16317	186	14	itc	itc	PROPN
ajst-16317	186	15	comparison	comparison	NOUN
ajst-16317	186	16	to	to	ADP
ajst-16317	186	17	itm	itm	PROPN
ajst-16317	186	18	comparison	comparison	NOUN
ajst-16317	186	19	.	.	PUNCT
ajst-16317	187	1	by	by	ADP
ajst-16317	187	2	using	use	VERB
ajst-16317	187	3	the	the	DET
ajst-16317	187	4	hard	hard	ADJ
ajst-16317	187	5	-	-	PUNCT
ajst-16317	187	6	sample	sample	NOUN
ajst-16317	187	7	strategy	strategy	NOUN
ajst-16317	187	8	to	to	PART
ajst-16317	187	9	improve	improve	VERB
ajst-16317	187	10	the	the	DET
ajst-16317	187	11	model	model	NOUN
ajst-16317	187	12	's	's	PART
ajst-16317	187	13	ability	ability	NOUN
ajst-16317	187	14	to	to	PART
ajst-16317	187	15	distinguish	distinguish	VERB
ajst-16317	187	16	between	between	ADP
ajst-16317	187	17	positive	positive	ADJ
ajst-16317	187	18	and	and	CCONJ
ajst-16317	187	19	negative	negative	ADJ
ajst-16317	187	20	samples	sample	NOUN
ajst-16317	187	21	,	,	PUNCT
ajst-16317	187	22	we	we	PRON
ajst-16317	187	23	further	far	ADV
ajst-16317	187	24	improve	improve	VERB
ajst-16317	187	25	the	the	DET
ajst-16317	187	26	model	model	NOUN
ajst-16317	187	27	's	's	PART
ajst-16317	187	28	retrieval	retrieval	ADJ
ajst-16317	187	29	accuracy	accuracy	NOUN
ajst-16317	187	30	.	.	PUNCT
ajst-16317	188	1	our	our	PRON
ajst-16317	188	2	model	model	NOUN
ajst-16317	188	3	was	be	AUX
ajst-16317	188	4	fine	fine	ADV
ajst-16317	188	5	-	-	PUNCT
ajst-16317	188	6	tuned	tune	VERB
ajst-16317	188	7	and	and	CCONJ
ajst-16317	188	8	inferenced	inference	VERB
ajst-16317	188	9	on	on	ADP
ajst-16317	188	10	the	the	DET
ajst-16317	188	11	aliproduct	aliproduct	NOUN
ajst-16317	188	12	data	datum	NOUN
ajst-16317	188	13	set	set	VERB
ajst-16317	188	14	proposed	propose	VERB
ajst-16317	188	15	by	by	ADP
ajst-16317	188	16	ali	ali	PROPN
ajst-16317	188	17	.	.	PUNCT
ajst-16317	188	18	experiments	experiment	NOUN
ajst-16317	188	19	show	show	VERB
ajst-16317	188	20	that	that	SCONJ
ajst-16317	188	21	without	without	ADP
ajst-16317	188	22	data	datum	NOUN
ajst-16317	188	23	cleaning	clean	VERB
ajst-16317	188	24	86	86	NUM
ajst-16317	188	25	and	and	CCONJ
ajst-16317	188	26	data	datum	NOUN
ajst-16317	188	27	enhancement	enhancement	NOUN
ajst-16317	188	28	such	such	ADJ
ajst-16317	188	29	as	as	ADP
ajst-16317	188	30	cap	cap	NOUN
ajst-16317	188	31	-	-	PUNCT
ajst-16317	188	32	fit	fit	NOUN
ajst-16317	188	33	,	,	PUNCT
ajst-16317	188	34	our	our	PRON
ajst-16317	188	35	model	model	NOUN
ajst-16317	188	36	can	can	AUX
ajst-16317	188	37	accurately	accurately	ADV
ajst-16317	188	38	retrieve	retrieve	VERB
ajst-16317	188	39	retrieval	retrieval	NOUN
ajst-16317	188	40	input	input	NOUN
ajst-16317	188	41	matching	matching	NOUN
ajst-16317	188	42	results	result	NOUN
ajst-16317	188	43	including	include	VERB
ajst-16317	188	44	chinese	chinese	ADJ
ajst-16317	188	45	and	and	CCONJ
ajst-16317	188	46	english	english	ADJ
ajst-16317	188	47	bilinguals	bilingual	NOUN
ajst-16317	188	48	.	.	PUNCT
ajst-16317	189	1	furthermore	furthermore	ADV
ajst-16317	189	2	,	,	PUNCT
ajst-16317	189	3	our	our	PRON
ajst-16317	189	4	model	model	NOUN
ajst-16317	189	5	can	can	AUX
ajst-16317	189	6	achieve	achieve	VERB
ajst-16317	189	7	a	a	DET
ajst-16317	189	8	single	single	ADJ
ajst-16317	189	9	target	target	NOUN
ajst-16317	189	10	retrieval	retrieval	NOUN
ajst-16317	189	11	speed	speed	NOUN
ajst-16317	189	12	of	of	ADP
ajst-16317	189	13	0.16s	0.16s	NUM
ajst-16317	189	14	on	on	ADP
ajst-16317	189	15	a	a	DET
ajst-16317	189	16	single	single	ADJ
ajst-16317	189	17	nvidia	nvidia	PROPN
ajst-16317	189	18	-	-	PUNCT
ajst-16317	189	19	a100	a100	PROPN
ajst-16317	189	20	gpu	gpu	NOUN
ajst-16317	189	21	.	.	PUNCT
ajst-16317	190	1	this	this	PRON
ajst-16317	190	2	demonstrates	demonstrate	VERB
ajst-16317	190	3	the	the	DET
ajst-16317	190	4	efficiency	efficiency	NOUN
ajst-16317	190	5	and	and	CCONJ
ajst-16317	190	6	ease	ease	NOUN
ajst-16317	190	7	of	of	ADP
ajst-16317	190	8	deployment	deployment	NOUN
ajst-16317	190	9	of	of	ADP
ajst-16317	190	10	our	our	PRON
ajst-16317	190	11	model	model	NOUN
ajst-16317	190	12	.	.	PUNCT
ajst-16317	191	1	references	reference	NOUN
ajst-16317	191	2	[	[	X
ajst-16317	191	3	1	1	NUM
ajst-16317	191	4	]	]	X
ajst-16317	191	5	li	li	PROPN
ajst-16317	191	6	j	j	PROPN
ajst-16317	191	7	,	,	PUNCT
ajst-16317	191	8	li	li	PROPN
ajst-16317	192	1	d	d	PROPN
ajst-16317	192	2	,	,	PUNCT
ajst-16317	192	3	xiong	xiong	PROPN
ajst-16317	192	4	c	c	AUX
ajst-16317	192	5	,	,	PUNCT
ajst-16317	193	1	et	et	PROPN
ajst-16317	193	2	al	al	PROPN
ajst-16317	193	3	.	.	PROPN
ajst-16317	193	4	blip	blip	NOUN
ajst-16317	193	5	:	:	PUNCT
ajst-16317	193	6	bootstrapping	bootstrappe	VERB
ajst-16317	193	7	language	language	NOUN
ajst-16317	193	8	-	-	PUNCT
ajst-16317	193	9	image	image	NOUN
ajst-16317	193	10	pre	pre	NOUN
ajst-16317	193	11	-	-	NOUN
ajst-16317	193	12	training	train	VERB
ajst-16317	193	13	for	for	ADP
ajst-16317	193	14	unified	unified	ADJ
ajst-16317	193	15	vision	vision	NOUN
ajst-16317	193	16	-	-	PUNCT
ajst-16317	193	17	language	language	NOUN
ajst-16317	193	18	understanding	understanding	NOUN
ajst-16317	193	19	and	and	CCONJ
ajst-16317	193	20	generation[c]//international	generation[c]//international	PROPN
ajst-16317	193	21	conference	conference	NOUN
ajst-16317	193	22	on	on	ADP
ajst-16317	193	23	machine	machine	NOUN
ajst-16317	193	24	learning	learning	NOUN
ajst-16317	193	25	.	.	PUNCT
ajst-16317	194	1	pmlr	pmlr	NOUN
ajst-16317	194	2	,	,	PUNCT
ajst-16317	194	3	2022	2022	NUM
ajst-16317	194	4	:	:	PUNCT
ajst-16317	194	5	12888	12888	NUM
ajst-16317	194	6	-	-	SYM
ajst-16317	194	7	12900	12900	NUM
ajst-16317	194	8	.	.	PUNCT
ajst-16317	195	1	[	[	X
ajst-16317	195	2	2	2	NUM
ajst-16317	195	3	]	]	X
ajst-16317	195	4	li	li	PROPN
ajst-16317	195	5	j	j	PROPN
ajst-16317	195	6	,	,	PUNCT
ajst-16317	195	7	li	li	PROPN
ajst-16317	195	8	d	d	PROPN
ajst-16317	195	9	,	,	PUNCT
ajst-16317	195	10	savarese	savarese	PROPN
ajst-16317	195	11	s	s	PROPN
ajst-16317	195	12	,	,	PUNCT
ajst-16317	195	13	et	et	PROPN
ajst-16317	195	14	al	al	PROPN
ajst-16317	195	15	.	.	PUNCT
ajst-16317	196	1	blip-2	blip-2	PROPN
ajst-16317	196	2	:	:	PUNCT
ajst-16317	196	3	bootstrapping	bootstrappe	VERB
ajst-16317	196	4	languageimage	languageimage	NOUN
ajst-16317	196	5	pre	pre	NOUN
ajst-16317	196	6	-	-	NOUN
ajst-16317	196	7	training	training	NOUN
ajst-16317	196	8	with	with	ADP
ajst-16317	196	9	frozen	frozen	ADJ
ajst-16317	196	10	image	image	NOUN
ajst-16317	196	11	encoders	encoder	NOUN
ajst-16317	196	12	and	and	CCONJ
ajst-16317	196	13	large	large	ADJ
ajst-16317	196	14	language	language	NOUN
ajst-16317	196	15	models[j	models[j	PROPN
ajst-16317	196	16	]	]	PUNCT
ajst-16317	196	17	.	.	PUNCT
ajst-16317	197	1	arxiv	arxiv	PROPN
ajst-16317	197	2	preprint	preprint	VERB
ajst-16317	197	3	arxiv:2301.12597	arxiv:2301.12597	PROPN
ajst-16317	197	4	,	,	PUNCT
ajst-16317	197	5	2023	2023	NUM
ajst-16317	197	6	.	.	PUNCT
ajst-16317	198	1	[	[	X
ajst-16317	198	2	3	3	X
ajst-16317	198	3	]	]	X
ajst-16317	198	4	li	li	PROPN
ajst-16317	198	5	d	d	PROPN
ajst-16317	198	6	,	,	PUNCT
ajst-16317	198	7	li	li	PROPN
ajst-16317	198	8	j	j	PROPN
ajst-16317	198	9	,	,	PUNCT
ajst-16317	198	10	hoi	hoi	PROPN
ajst-16317	198	11	s	s	PROPN
ajst-16317	198	12	c	c	PROPN
ajst-16317	198	13	h.	h.	PROPN
ajst-16317	198	14	blip	blip	PROPN
ajst-16317	198	15	-	-	PUNCT
ajst-16317	198	16	diffusion	diffusion	NOUN
ajst-16317	198	17	:	:	PUNCT
ajst-16317	198	18	pre	pre	ADJ
ajst-16317	198	19	-	-	ADJ
ajst-16317	198	20	trained	train	VERB
ajst-16317	198	21	subject	subject	NOUN
ajst-16317	198	22	representation	representation	NOUN
ajst-16317	198	23	for	for	ADP
ajst-16317	198	24	controllable	controllable	ADJ
ajst-16317	198	25	text	text	NOUN
ajst-16317	198	26	-	-	PUNCT
ajst-16317	198	27	to	to	ADP
ajst-16317	198	28	-	-	PUNCT
ajst-16317	198	29	image	image	NOUN
ajst-16317	198	30	generation	generation	NOUN
ajst-16317	198	31	and	and	CCONJ
ajst-16317	198	32	editing[j	editing[j	NOUN
ajst-16317	198	33	]	]	PUNCT
ajst-16317	198	34	.	.	PUNCT
ajst-16317	199	1	arxiv	arxiv	PROPN
ajst-16317	199	2	preprint	preprint	NOUN
ajst-16317	199	3	arxiv:2305.14720	arxiv:2305.14720	NOUN
ajst-16317	199	4	,	,	PUNCT
ajst-16317	199	5	2023	2023	NUM
ajst-16317	199	6	.	.	PUNCT
ajst-16317	200	1	[	[	X
ajst-16317	200	2	4	4	X
ajst-16317	200	3	]	]	PUNCT
ajst-16317	200	4	she	she	PRON
ajst-16317	200	5	h	h	NOUN
ajst-16317	200	6	,	,	PUNCT
ajst-16317	200	7	chen	chen	PROPN
ajst-16317	200	8	r	r	PROPN
ajst-16317	200	9	r	r	PROPN
ajst-16317	200	10	,	,	PUNCT
ajst-16317	200	11	liang	liang	PROPN
ajst-16317	200	12	d	d	PROPN
ajst-16317	200	13	,	,	PUNCT
ajst-16317	200	14	et	et	PROPN
ajst-16317	200	15	al	al	PROPN
ajst-16317	200	16	.	.	PROPN
ajst-16317	200	17	sparse	sparse	ADJ
ajst-16317	200	18	blip	blip	NOUN
ajst-16317	200	19	:	:	PUNCT
ajst-16317	200	20	blind	blind	ADJ
ajst-16317	200	21	iterative	iterative	NOUN
ajst-16317	200	22	parallel	parallel	ADJ
ajst-16317	200	23	imaging	imaging	NOUN
ajst-16317	200	24	reconstruction	reconstruction	NOUN
ajst-16317	200	25	using	use	VERB
ajst-16317	200	26	compressed	compressed	ADJ
ajst-16317	200	27	sensing[j	sensing[j	NOUN
ajst-16317	200	28	]	]	PUNCT
ajst-16317	200	29	.	.	PUNCT
ajst-16317	201	1	magnetic	magnetic	ADJ
ajst-16317	201	2	resonance	resonance	NOUN
ajst-16317	201	3	in	in	ADP
ajst-16317	201	4	medicine	medicine	NOUN
ajst-16317	201	5	,	,	PUNCT
ajst-16317	201	6	2014	2014	NUM
ajst-16317	201	7	,	,	PUNCT
ajst-16317	201	8	71(2	71(2	NUM
ajst-16317	201	9	):	):	PUNCT
ajst-16317	201	10	645	645	NUM
ajst-16317	201	11	-	-	SYM
ajst-16317	201	12	660	660	NUM
ajst-16317	201	13	.	.	PUNCT
ajst-16317	202	1	[	[	X
ajst-16317	202	2	5	5	X
ajst-16317	202	3	]	]	PUNCT
ajst-16317	202	4	yarach	yarach	PROPN
ajst-16317	202	5	u	u	NOUN
ajst-16317	202	6	,	,	PUNCT
ajst-16317	202	7	chatnuntawech	chatnuntawech	NOUN
ajst-16317	202	8	i	i	PRON
ajst-16317	202	9	,	,	PUNCT
ajst-16317	202	10	liao	liao	PROPN
ajst-16317	202	11	c	c	PROPN
ajst-16317	202	12	,	,	PUNCT
ajst-16317	202	13	et	et	PROPN
ajst-16317	202	14	al	al	PROPN
ajst-16317	202	15	.	.	PUNCT
ajst-16317	202	16	blip	blip	NOUN
ajst-16317	202	17	-	-	PUNCT
ajst-16317	202	18	up	up	ADP
ajst-16317	202	19	blip	blip	NOUN
ajst-16317	202	20	-	-	PUNCT
ajst-16317	202	21	down	down	ADP
ajst-16317	202	22	circular	circular	ADJ
ajst-16317	202	23	epi	epi	NOUN
ajst-16317	202	24	(	(	PUNCT
ajst-16317	202	25	buda	buda	NOUN
ajst-16317	202	26	-	-	PUNCT
ajst-16317	202	27	cepi	cepi	PROPN
ajst-16317	202	28	)	)	PUNCT
ajst-16317	202	29	for	for	ADP
ajst-16317	202	30	distortion	distortion	NOUN
ajst-16317	202	31	-	-	PUNCT
ajst-16317	202	32	free	free	ADJ
ajst-16317	202	33	dmri	dmri	NOUN
ajst-16317	202	34	with	with	ADP
ajst-16317	202	35	rapid	rapid	ADJ
ajst-16317	202	36	unrolled	unrolled	ADJ
ajst-16317	202	37	deep	deep	ADJ
ajst-16317	202	38	learning	learn	VERB
ajst-16317	202	39	reconstruction[j	reconstruction[j	PROPN
ajst-16317	202	40	]	]	PUNCT
ajst-16317	202	41	.	.	PUNCT
ajst-16317	203	1	arxiv	arxiv	PROPN
ajst-16317	203	2	preprint	preprint	PROPN
ajst-16317	203	3	arxiv:2310.15939	arxiv:2310.15939	PROPN
ajst-16317	203	4	,	,	PUNCT
ajst-16317	203	5	2023	2023	NUM
ajst-16317	203	6	.	.	PUNCT
ajst-16317	204	1	[	[	X
ajst-16317	204	2	6	6	NUM
ajst-16317	204	3	]	]	X
ajst-16317	204	4	chiang	chiang	PROPN
ajst-16317	204	5	c	c	PROPN
ajst-16317	204	6	y	y	PROPN
ajst-16317	204	7	,	,	PUNCT
ajst-16317	204	8	chang	chang	PROPN
ajst-16317	204	9	i	i	PRON
ajst-16317	204	10	h	h	VERB
ajst-16317	204	11	,	,	PUNCT
ajst-16317	204	12	liao	liao	PROPN
ajst-16317	204	13	s	s	PROPN
ajst-16317	204	14	w.	w.	PROPN
ajst-16317	204	15	blip	blip	PROPN
ajst-16317	204	16	-	-	PUNCT
ajst-16317	204	17	adapter	adapter	NOUN
ajst-16317	204	18	:	:	PUNCT
ajst-16317	204	19	parameterefficient	parameterefficient	NOUN
ajst-16317	204	20	transfer	transfer	NOUN
ajst-16317	204	21	learning	learn	VERB
ajst-16317	204	22	for	for	ADP
ajst-16317	204	23	mobile	mobile	ADJ
ajst-16317	204	24	screenshot	screenshot	NOUN
ajst-16317	204	25	captioning[j	captioning[j	NOUN
ajst-16317	204	26	]	]	PUNCT
ajst-16317	204	27	.	.	PUNCT
ajst-16317	205	1	arxiv	arxiv	PROPN
ajst-16317	205	2	preprint	preprint	NOUN
ajst-16317	205	3	arxiv:2309.14774	arxiv:2309.14774	NOUN
ajst-16317	205	4	,	,	PUNCT
ajst-16317	205	5	2023	2023	NUM
ajst-16317	205	6	.	.	PUNCT
ajst-16317	206	1	[	[	X
ajst-16317	206	2	7	7	X
ajst-16317	206	3	]	]	X
ajst-16317	206	4	savić	savić	PROPN
ajst-16317	206	5	t	t	PROPN
ajst-16317	206	6	,	,	PUNCT
ajst-16317	206	7	brun	brun	PROPN
ajst-16317	206	8	-	-	PUNCT
ajst-16317	206	9	laguna	laguna	PROPN
ajst-16317	206	10	k	k	PROPN
ajst-16317	206	11	,	,	PUNCT
ajst-16317	206	12	watteyne	watteyne	NOUN
ajst-16317	206	13	t.	t.	PROPN
ajst-16317	206	14	blip	blip	NOUN
ajst-16317	206	15	:	:	PUNCT
ajst-16317	206	16	identifying	identify	VERB
ajst-16317	206	17	boats	boat	NOUN
ajst-16317	206	18	in	in	ADP
ajst-16317	206	19	a	a	DET
ajst-16317	206	20	smart	smart	ADJ
ajst-16317	206	21	marina	marina	NOUN
ajst-16317	206	22	environment[c]//2023	environment[c]//2023	NUM
ajst-16317	206	23	19th	19th	ADJ
ajst-16317	206	24	international	international	ADJ
ajst-16317	206	25	conference	conference	NOUN
ajst-16317	206	26	on	on	ADP
ajst-16317	206	27	distributed	distribute	VERB
ajst-16317	206	28	computing	computing	NOUN
ajst-16317	206	29	in	in	ADP
ajst-16317	206	30	smart	smart	ADJ
ajst-16317	206	31	systems	system	NOUN
ajst-16317	206	32	and	and	CCONJ
ajst-16317	206	33	the	the	DET
ajst-16317	206	34	internet	internet	NOUN
ajst-16317	206	35	of	of	ADP
ajst-16317	206	36	things	thing	NOUN
ajst-16317	206	37	(	(	PUNCT
ajst-16317	206	38	dcoss	dcoss	NOUN
ajst-16317	206	39	-	-	NOUN
ajst-16317	206	40	iot	iot	NOUN
ajst-16317	206	41	)	)	PUNCT
ajst-16317	206	42	.	.	PUNCT
ajst-16317	207	1	ieee	ieee	NOUN
ajst-16317	207	2	,	,	PUNCT
ajst-16317	207	3	2023	2023	NUM
ajst-16317	207	4	:	:	PUNCT
ajst-16317	207	5	710	710	NUM
ajst-16317	207	6	-	-	SYM
ajst-16317	207	7	714	714	NUM
ajst-16317	207	8	.	.	PUNCT
ajst-16317	208	1	[	[	X
ajst-16317	208	2	8	8	NUM
ajst-16317	208	3	]	]	X
ajst-16317	208	4	lee	lee	PROPN
ajst-16317	208	5	c	c	PROPN
ajst-16317	208	6	,	,	PUNCT
ajst-16317	208	7	jang	jang	PROPN
ajst-16317	208	8	j	j	PROPN
ajst-16317	208	9	,	,	PUNCT
ajst-16317	208	10	lee	lee	PROPN
ajst-16317	208	11	j.	j.	PROPN
ajst-16317	208	12	personalizing	personalize	VERB
ajst-16317	208	13	text	text	NOUN
ajst-16317	208	14	-	-	PUNCT
ajst-16317	208	15	to	to	ADP
ajst-16317	208	16	-	-	PUNCT
ajst-16317	208	17	image	image	NOUN
ajst-16317	208	18	generation	generation	NOUN
ajst-16317	208	19	with	with	ADP
ajst-16317	208	20	visual	visual	ADJ
ajst-16317	208	21	prompts	prompt	NOUN
ajst-16317	208	22	using	use	VERB
ajst-16317	208	23	blip-2[j	blip-2[j	NUM
ajst-16317	208	24	]	]	PUNCT
ajst-16317	208	25	.	.	PUNCT
ajst-16317	209	1	2023	2023	NUM
ajst-16317	209	2	.	.	PUNCT
ajst-16317	210	1	[	[	X
ajst-16317	210	2	9	9	NUM
ajst-16317	210	3	]	]	SYM
ajst-16317	210	4	wu	wu	PROPN
ajst-16317	210	5	j	j	PROPN
ajst-16317	210	6	,	,	PUNCT
ajst-16317	210	7	cui	cui	PROPN
ajst-16317	210	8	z	z	PROPN
ajst-16317	210	9	,	,	PUNCT
ajst-16317	210	10	sheng	sheng	PROPN
ajst-16317	210	11	v	v	ADP
ajst-16317	210	12	s	s	PROPN
ajst-16317	210	13	,	,	PUNCT
ajst-16317	210	14	et	et	PROPN
ajst-16317	210	15	al	al	PROPN
ajst-16317	210	16	.	.	PUNCT
ajst-16317	211	1	a	a	DET
ajst-16317	211	2	comparative	comparative	ADJ
ajst-16317	211	3	study	study	NOUN
ajst-16317	211	4	of	of	ADP
ajst-16317	211	5	sift	sift	NOUN
ajst-16317	211	6	and	and	CCONJ
ajst-16317	211	7	its	its	PRON
ajst-16317	211	8	variants[j	variants[j	NOUN
ajst-16317	211	9	]	]	PUNCT
ajst-16317	211	10	.	.	PUNCT
ajst-16317	212	1	measurement	measurement	PROPN
ajst-16317	212	2	science	science	PROPN
ajst-16317	212	3	review	review	PROPN
ajst-16317	212	4	,	,	PUNCT
ajst-16317	212	5	2013	2013	NUM
ajst-16317	212	6	,	,	PUNCT
ajst-16317	212	7	13(3	13(3	NUM
ajst-16317	212	8	):	):	PUNCT
ajst-16317	212	9	122	122	NUM
ajst-16317	212	10	-	-	SYM
ajst-16317	212	11	131	131	NUM
ajst-16317	212	12	.	.	PUNCT
ajst-16317	213	1	[	[	X
ajst-16317	213	2	10	10	NUM
ajst-16317	213	3	]	]	PUNCT
ajst-16317	213	4	otero	otero	PROPN
ajst-16317	213	5	i	i	PRON
ajst-16317	213	6	r.	r.	VERB
ajst-16317	213	7	anatomy	anatomy	NOUN
ajst-16317	213	8	of	of	ADP
ajst-16317	213	9	the	the	DET
ajst-16317	213	10	sift	sift	NOUN
ajst-16317	213	11	method[d	method[d	PROPN
ajst-16317	213	12	]	]	PUNCT
ajst-16317	213	13	.	.	PUNCT
ajst-16317	214	1	école	école	PROPN
ajst-16317	214	2	normale	normale	PROPN
ajst-16317	214	3	supérieure	supérieure	PROPN
ajst-16317	214	4	de	de	PROPN
ajst-16317	214	5	cachan	cachan	PROPN
ajst-16317	214	6	-	-	PUNCT
ajst-16317	214	7	ens	ens	PROPN
ajst-16317	214	8	cachan	cachan	PROPN
ajst-16317	214	9	,	,	PUNCT
ajst-16317	214	10	2015	2015	NUM
ajst-16317	214	11	.	.	PUNCT
ajst-16317	215	1	[	[	X
ajst-16317	215	2	11	11	NUM
ajst-16317	215	3	]	]	X
ajst-16317	215	4	bay	bay	NOUN
ajst-16317	215	5	h	h	NOUN
ajst-16317	215	6	,	,	PUNCT
ajst-16317	215	7	tuytelaars	tuytelaar	VERB
ajst-16317	215	8	t	t	PROPN
ajst-16317	215	9	,	,	PUNCT
ajst-16317	215	10	van	van	PROPN
ajst-16317	215	11	gool	gool	PROPN
ajst-16317	215	12	l.	l.	PROPN
ajst-16317	215	13	surf	surf	PROPN
ajst-16317	215	14	:	:	PUNCT
ajst-16317	215	15	speeded	speed	VERB
ajst-16317	215	16	up	up	ADP
ajst-16317	215	17	robust	robust	ADJ
ajst-16317	215	18	features[c]//computer	features[c]//computer	PROPN
ajst-16317	215	19	vision	vision	NOUN
ajst-16317	215	20	–	–	PUNCT
ajst-16317	215	21	eccv	eccv	ADJ
ajst-16317	215	22	2006	2006	NUM
ajst-16317	215	23	:	:	PUNCT
ajst-16317	215	24	9th	9th	ADJ
ajst-16317	215	25	european	european	ADJ
ajst-16317	215	26	conference	conference	NOUN
ajst-16317	215	27	on	on	ADP
ajst-16317	215	28	computer	computer	NOUN
ajst-16317	215	29	vision	vision	NOUN
ajst-16317	215	30	,	,	PUNCT
ajst-16317	215	31	graz	graz	PROPN
ajst-16317	215	32	,	,	PUNCT
ajst-16317	215	33	austria	austria	PROPN
ajst-16317	215	34	,	,	PUNCT
ajst-16317	215	35	may	may	AUX
ajst-16317	215	36	7	7	NUM
ajst-16317	215	37	-	-	SYM
ajst-16317	215	38	13	13	NUM
ajst-16317	215	39	,	,	PUNCT
ajst-16317	215	40	2006	2006	NUM
ajst-16317	215	41	.	.	PUNCT
ajst-16317	216	1	proceedings	proceeding	NOUN
ajst-16317	216	2	,	,	PUNCT
ajst-16317	216	3	part	part	NOUN
ajst-16317	216	4	i	i	PRON
ajst-16317	216	5	9	9	NUM
ajst-16317	216	6	.	.	PUNCT
ajst-16317	216	7	springer	springer	PROPN
ajst-16317	216	8	berlin	berlin	PROPN
ajst-16317	216	9	heidelberg	heidelberg	PROPN
ajst-16317	216	10	,	,	PUNCT
ajst-16317	216	11	2006	2006	NUM
ajst-16317	216	12	:	:	PUNCT
ajst-16317	216	13	404	404	NUM
ajst-16317	216	14	-	-	SYM
ajst-16317	216	15	417	417	NUM
ajst-16317	216	16	.	.	PUNCT
ajst-16317	217	1	[	[	X
ajst-16317	217	2	12	12	NUM
ajst-16317	217	3	]	]	PUNCT
ajst-16317	217	4	verma	verma	PROPN
ajst-16317	217	5	n	n	PROPN
ajst-16317	217	6	k	k	PROPN
ajst-16317	217	7	,	,	PUNCT
ajst-16317	217	8	goyal	goyal	PROPN
ajst-16317	217	9	a	a	X
ajst-16317	217	10	,	,	PUNCT
ajst-16317	217	11	vardhan	vardhan	PROPN
ajst-16317	217	12	a	a	DET
ajst-16317	217	13	h	h	NOUN
ajst-16317	217	14	,	,	PUNCT
ajst-16317	217	15	et	et	PROPN
ajst-16317	217	16	al	al	PROPN
ajst-16317	217	17	.	.	PROPN
ajst-16317	217	18	object	object	PROPN
ajst-16317	217	19	matching	matching	NOUN
ajst-16317	217	20	using	use	VERB
ajst-16317	217	21	speeded	speed	VERB
ajst-16317	217	22	up	up	ADP
ajst-16317	217	23	robust	robust	ADJ
ajst-16317	217	24	features[c]//intelligent	features[c]//intelligent	PROPN
ajst-16317	217	25	and	and	CCONJ
ajst-16317	217	26	evolutionary	evolutionary	ADJ
ajst-16317	217	27	systems	system	NOUN
ajst-16317	217	28	:	:	PUNCT
ajst-16317	217	29	the	the	DET
ajst-16317	217	30	19th	19th	ADJ
ajst-16317	217	31	asia	asia	PROPN
ajst-16317	217	32	pacific	pacific	PROPN
ajst-16317	217	33	symposium	symposium	PROPN
ajst-16317	217	34	,	,	PUNCT
ajst-16317	217	35	ies	ies	PROPN
ajst-16317	217	36	2015	2015	NUM
ajst-16317	217	37	,	,	PUNCT
ajst-16317	217	38	bangkok	bangkok	PROPN
ajst-16317	217	39	,	,	PUNCT
ajst-16317	217	40	thailand	thailand	PROPN
ajst-16317	217	41	,	,	PUNCT
ajst-16317	217	42	november	november	PROPN
ajst-16317	217	43	2015	2015	NUM
ajst-16317	217	44	,	,	PUNCT
ajst-16317	217	45	proceedings	proceeding	NOUN
ajst-16317	217	46	.	.	PUNCT
ajst-16317	218	1	springer	springer	NOUN
ajst-16317	218	2	international	international	ADJ
ajst-16317	218	3	publishing	publishing	NOUN
ajst-16317	218	4	,	,	PUNCT
ajst-16317	218	5	2016	2016	NUM
ajst-16317	218	6	:	:	PUNCT
ajst-16317	219	1	415	415	NUM
ajst-16317	219	2	-	-	SYM
ajst-16317	219	3	427	427	NUM
ajst-16317	219	4	.	.	PUNCT
ajst-16317	220	1	[	[	X
ajst-16317	220	2	13	13	NUM
ajst-16317	220	3	]	]	X
ajst-16317	220	4	leutenegger	leutenegger	NOUN
ajst-16317	220	5	s	s	PROPN
ajst-16317	220	6	,	,	PUNCT
ajst-16317	220	7	chli	chli	NOUN
ajst-16317	220	8	m	m	PROPN
ajst-16317	220	9	,	,	PUNCT
ajst-16317	220	10	siegwart	siegwart	ADJ
ajst-16317	220	11	r	r	NOUN
ajst-16317	220	12	y.	y.	NOUN
ajst-16317	220	13	brisk	brisk	NOUN
ajst-16317	220	14	:	:	PUNCT
ajst-16317	220	15	binary	binary	ADJ
ajst-16317	220	16	robust	robust	ADJ
ajst-16317	220	17	invariant	invariant	ADJ
ajst-16317	220	18	scalable	scalable	ADJ
ajst-16317	220	19	keypoints[c]//2011	keypoints[c]//2011	PROPN
ajst-16317	220	20	international	international	ADJ
ajst-16317	220	21	conference	conference	NOUN
ajst-16317	220	22	on	on	ADP
ajst-16317	220	23	computer	computer	NOUN
ajst-16317	220	24	vision	vision	NOUN
ajst-16317	220	25	.	.	PUNCT
ajst-16317	221	1	ieee	ieee	PROPN
ajst-16317	221	2	,	,	PUNCT
ajst-16317	221	3	2011	2011	NUM
ajst-16317	221	4	:	:	PUNCT
ajst-16317	221	5	2548	2548	NUM
ajst-16317	221	6	-	-	SYM
ajst-16317	221	7	2555	2555	NUM
ajst-16317	221	8	.	.	PUNCT
ajst-16317	222	1	[	[	X
ajst-16317	222	2	14	14	NUM
ajst-16317	222	3	]	]	PUNCT
ajst-16317	222	4	aglave	aglave	NOUN
ajst-16317	222	5	p	p	NOUN
ajst-16317	222	6	,	,	PUNCT
ajst-16317	222	7	kolkure	kolkure	NOUN
ajst-16317	222	8	v	v	ADP
ajst-16317	222	9	s.	s.	PROPN
ajst-16317	222	10	implementation	implementation	NOUN
ajst-16317	222	11	of	of	ADP
ajst-16317	222	12	high	high	ADJ
ajst-16317	222	13	performance	performance	NOUN
ajst-16317	222	14	feature	feature	NOUN
ajst-16317	222	15	extraction	extraction	NOUN
ajst-16317	222	16	method	method	NOUN
ajst-16317	222	17	using	use	VERB
ajst-16317	222	18	oriented	orient	VERB
ajst-16317	222	19	fast	fast	ADJ
ajst-16317	222	20	and	and	CCONJ
ajst-16317	222	21	rotated	rotate	VERB
ajst-16317	222	22	brief	brief	NOUN
ajst-16317	222	23	algorithm[j	algorithm[j	PROPN
ajst-16317	222	24	]	]	PUNCT
ajst-16317	222	25	.	.	PUNCT
ajst-16317	223	1	int	int	NOUN
ajst-16317	223	2	.	.	PUNCT
ajst-16317	224	1	j.	j.	PROPN
ajst-16317	224	2	res	res	PROPN
ajst-16317	224	3	.	.	PUNCT
ajst-16317	225	1	eng	eng	PROPN
ajst-16317	225	2	.	.	PROPN
ajst-16317	225	3	technol	technol	PROPN
ajst-16317	225	4	,	,	PUNCT
ajst-16317	225	5	2015	2015	NUM
ajst-16317	225	6	,	,	PUNCT
ajst-16317	225	7	4	4	NUM
ajst-16317	225	8	:	:	SYM
ajst-16317	225	9	394	394	NUM
ajst-16317	225	10	-	-	SYM
ajst-16317	225	11	397	397	NUM
ajst-16317	225	12	.	.	PUNCT
ajst-16317	226	1	[	[	X
ajst-16317	226	2	15	15	NUM
ajst-16317	226	3	]	]	X
ajst-16317	226	4	danielsson	danielsson	NOUN
ajst-16317	226	5	p	p	PROPN
ajst-16317	226	6	e.	e.	PROPN
ajst-16317	226	7	euclidean	euclidean	PROPN
ajst-16317	226	8	distance	distance	NOUN
ajst-16317	226	9	mapping[j	mapping[j	NOUN
ajst-16317	226	10	]	]	PUNCT
ajst-16317	226	11	.	.	PUNCT
ajst-16317	227	1	computer	computer	NOUN
ajst-16317	227	2	graphics	graphic	NOUN
ajst-16317	227	3	and	and	CCONJ
ajst-16317	227	4	image	image	NOUN
ajst-16317	227	5	processing	processing	NOUN
ajst-16317	227	6	,	,	PUNCT
ajst-16317	227	7	1980	1980	NUM
ajst-16317	227	8	,	,	PUNCT
ajst-16317	227	9	14(3	14(3	NUM
ajst-16317	227	10	):	):	PUNCT
ajst-16317	227	11	227	227	NUM
ajst-16317	227	12	-	-	SYM
ajst-16317	227	13	248	248	NUM
ajst-16317	227	14	.	.	PUNCT
ajst-16317	228	1	[	[	X
ajst-16317	228	2	16	16	NUM
ajst-16317	228	3	]	]	X
ajst-16317	228	4	malkauthekar	malkauthekar	PROPN
ajst-16317	228	5	m	m	PROPN
ajst-16317	228	6	d.	d.	PROPN
ajst-16317	228	7	analysis	analysis	NOUN
ajst-16317	228	8	of	of	ADP
ajst-16317	228	9	euclidean	euclidean	ADJ
ajst-16317	228	10	distance	distance	NOUN
ajst-16317	228	11	and	and	CCONJ
ajst-16317	228	12	manhattan	manhattan	PROPN
ajst-16317	228	13	distance	distance	NOUN
ajst-16317	228	14	measure	measure	NOUN
ajst-16317	228	15	in	in	ADP
ajst-16317	228	16	face	face	NOUN
ajst-16317	228	17	recognition[c]//third	recognition[c]//third	PROPN
ajst-16317	228	18	international	international	ADJ
ajst-16317	228	19	conference	conference	NOUN
ajst-16317	228	20	on	on	ADP
ajst-16317	228	21	computational	computational	ADJ
ajst-16317	228	22	intelligence	intelligence	NOUN
ajst-16317	228	23	and	and	CCONJ
ajst-16317	228	24	information	information	NOUN
ajst-16317	228	25	technology	technology	NOUN
ajst-16317	228	26	(	(	PUNCT
ajst-16317	228	27	ciit	ciit	NOUN
ajst-16317	228	28	2013	2013	NUM
ajst-16317	228	29	)	)	PUNCT
ajst-16317	228	30	.	.	PUNCT
ajst-16317	229	1	iet	iet	PROPN
ajst-16317	229	2	,	,	PUNCT
ajst-16317	229	3	2013	2013	NUM
ajst-16317	229	4	:	:	PUNCT
ajst-16317	229	5	503	503	NUM
ajst-16317	229	6	-	-	SYM
ajst-16317	229	7	507	507	NUM
ajst-16317	229	8	.	.	PUNCT
ajst-16317	230	1	[	[	X
ajst-16317	230	2	17	17	NUM
ajst-16317	230	3	]	]	X
ajst-16317	230	4	guo	guo	PROPN
ajst-16317	230	5	q	q	PROPN
ajst-16317	230	6	,	,	PUNCT
ajst-16317	230	7	wang	wang	PROPN
ajst-16317	230	8	c	c	PROPN
ajst-16317	230	9	,	,	PUNCT
ajst-16317	230	10	xiao	xiao	PROPN
ajst-16317	230	11	d	d	PROPN
ajst-16317	230	12	,	,	PUNCT
ajst-16317	230	13	et	et	PROPN
ajst-16317	230	14	al	al	PROPN
ajst-16317	230	15	.	.	PUNCT
ajst-16317	231	1	a	a	DET
ajst-16317	231	2	lightweight	lightweight	ADJ
ajst-16317	231	3	open	open	ADJ
ajst-16317	231	4	-	-	PUNCT
ajst-16317	231	5	world	world	NOUN
ajst-16317	231	6	pest	pest	NOUN
ajst-16317	231	7	image	image	NOUN
ajst-16317	231	8	classifier	classifier	NOUN
ajst-16317	231	9	using	use	VERB
ajst-16317	231	10	resnet8	resnet8	NOUN
ajst-16317	231	11	-	-	PUNCT
ajst-16317	231	12	based	base	VERB
ajst-16317	231	13	matching	matching	NOUN
ajst-16317	231	14	network	network	NOUN
ajst-16317	231	15	and	and	CCONJ
ajst-16317	231	16	nt	not	PART
ajst-16317	231	17	-	-	PUNCT
ajst-16317	231	18	xent	xent	ADJ
ajst-16317	231	19	loss	loss	NOUN
ajst-16317	231	20	function[j	function[j	PROPN
ajst-16317	231	21	]	]	PUNCT
ajst-16317	231	22	.	.	PUNCT
ajst-16317	232	1	expert	expert	NOUN
ajst-16317	232	2	systems	system	NOUN
ajst-16317	232	3	with	with	ADP
ajst-16317	232	4	applications	application	NOUN
ajst-16317	232	5	,	,	PUNCT
ajst-16317	232	6	2024	2024	NUM
ajst-16317	232	7	,	,	PUNCT
ajst-16317	232	8	237	237	NUM
ajst-16317	232	9	:	:	SYM
ajst-16317	232	10	121395	121395	NUM
ajst-16317	232	11	.	.	PUNCT
ajst-16317	233	1	[	[	X
ajst-16317	233	2	18	18	NUM
ajst-16317	233	3	]	]	X
ajst-16317	233	4	steinlechner	steinlechner	NOUN
ajst-16317	233	5	s	s	PROPN
ajst-16317	233	6	,	,	PUNCT
ajst-16317	233	7	rohweder	rohweder	NOUN
ajst-16317	233	8	n	n	PROPN
ajst-16317	233	9	o	o	NOUN
ajst-16317	233	10	,	,	PUNCT
ajst-16317	233	11	korobko	korobko	PROPN
ajst-16317	233	12	m	m	PROPN
ajst-16317	233	13	,	,	PUNCT
ajst-16317	233	14	et	et	PROPN
ajst-16317	233	15	al	al	PROPN
ajst-16317	233	16	.	.	PROPN
ajst-16317	233	17	mitigating	mitigate	VERB
ajst-16317	233	18	mode	mode	NOUN
ajst-16317	233	19	-	-	PUNCT
ajst-16317	233	20	matching	match	VERB
ajst-16317	233	21	loss	loss	NOUN
ajst-16317	233	22	in	in	ADP
ajst-16317	233	23	nonclassical	nonclassical	ADJ
ajst-16317	233	24	laser	laser	NOUN
ajst-16317	233	25	interferometry[j	interferometry[j	NOUN
ajst-16317	233	26	]	]	PUNCT
ajst-16317	233	27	.	.	PUNCT
ajst-16317	234	1	physical	physical	ADJ
ajst-16317	234	2	review	review	NOUN
ajst-16317	234	3	letters	letter	NOUN
ajst-16317	234	4	,	,	PUNCT
ajst-16317	234	5	2018	2018	NUM
ajst-16317	234	6	,	,	PUNCT
ajst-16317	234	7	121(26	121(26	NUM
ajst-16317	234	8	):	):	PUNCT
ajst-16317	234	9	263602	263602	NUM
ajst-16317	234	10	.	.	PUNCT