Retrieve, Generate, Evaluate: A Case Study for Medical Paraphrases Generation with Small Language Models

Autor:	Buhnila, Ioana, Sinha, Aman, Constant, Mathieu
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	Recent surge in the accessibility of large language models (LLMs) to the general population can lead to untrackable use of such models for medical-related recommendations. Language generation via LLMs models has two key problems: firstly, they are prone to hallucination and therefore, for any medical purpose they require scientific and factual grounding; secondly, LLMs pose tremendous challenge to computational resources due to their gigantic model size. In this work, we introduce pRAGe, a pipeline for Retrieval Augmented Generation and evaluation of medical paraphrases generation using Small Language Models (SLM). We study the effectiveness of SLMs and the impact of external knowledge base for medical paraphrase generation in French. Comment: KnowledgeableLM 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.16565 Zobrazit plný text záznamu View this record from Arxiv