Feb. 26, 2024, 5:43 a.m. | Yang Deng, Yong Zhao, Moxin Li, See-Kiong Ng, Tat-Seng Chua

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.15062v1 Announce Type: cross
Abstract: Despite the remarkable abilities of Large Language Models (LLMs) to answer questions, they often display a considerable level of overconfidence even when the question does not have a definitive answer. To avoid providing hallucinated answers to these unknown questions, existing studies typically investigate approaches to refusing to answer these questions. In this work, we propose a novel and scalable self-alignment method to utilize the LLM itself to enhance its response-ability to different types of unknown …

abstract arxiv cs.cl cs.lg language language models large language large language models llms question questions trick type

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