KS-LLM: Knowledge Selection of Large Language Models with Evidence Document for Question Answering

arXiv:2404.15660v1 Announce Type: new
Abstract: Large language models (LLMs) suffer from the hallucination problem and face significant challenges when applied to knowledge-intensive tasks. A promising approach is to leverage evidence documents as extra supporting knowledge, which can be obtained through retrieval or generation. However, existing methods directly leverage the entire contents of the evidence document, which may introduce noise information and impair the performance of large language models. To tackle this problem, we propose a novel Knowledge Selection of Large …

abstract arxiv challenges cs.cl document documents evidence extra face hallucination however knowledge language language models large language large language models llm llms question question answering retrieval tasks through type