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When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively
May 1, 2024, 4:48 a.m. | Tiziano Labruna, Jon Ander Campos, Gorka Azkune
cs.CL updates on arXiv.org arxiv.org
Abstract: In this paper, we demonstrate how Large Language Models (LLMs) can effectively learn to use an off-the-shelf information retrieval (IR) system specifically when additional context is required to answer a given question. Given the performance of IR systems, the optimal strategy for question answering does not always entail external information retrieval; rather, it often involves leveraging the parametric memory of the LLM itself. Prior research has identified this phenomenon in the PopQA dataset, wherein the …
abstract arxiv context cs.cl cs.ir information language language models large language large language models learn llms paper performance question question answering retrieval strategy systems teaching type
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