May 16, 2024, 4:43 a.m. | Zihan Liu, Wei Ping, Rajarshi Roy, Peng Xu, Chankyu Lee, Mohammad Shoeybi, Bryan Catanzaro

cs.LG updates on arXiv.org arxiv.org

arXiv:2401.10225v3 Announce Type: replace-cross
Abstract: In this work, we introduce ChatQA, a suite of models that outperform GPT-4 on retrieval-augmented generation (RAG) and conversational question answering (QA). To enhance generation, we propose a two-stage instruction tuning method that significantly boosts the performance of RAG. For effective retrieval, we introduce a dense retriever optimized for conversational QA, which yields results comparable to the alternative state-of-the-art query rewriting models, while substantially reducing deployment costs. We also present the ChatRAG Bench, which encompasses …

arxiv conversational cs.ai cs.cl cs.ir cs.lg gpt gpt-4 rag replace type

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