id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
american_scientific_journal-12048	Olesia Khrapunova	Bridging Zero-Shot and Fine-Tuned Performance in Text Classification through Retrieval-Augmented Prompting	2025	17	.pdf	application/pdf	6851	347	50	In doing do, it connects the comparative analyses of model performance with recent advances in prompt optimization, exploring how established techniques can be systematically applied to bridge the long- standing gap between zero-shot LLMs and smaller fine-tuned encoder models. Problem Description Large Language Models (LLMs) have demonstrated impressive capabilities in zero-shot and few-shot settings, enabling practitioners to perform text classification without task-specific training data.	cache/american_scientific_journal-12048.pdf	txt/american_scientific_journal-12048.txt