May 7, 2024, 4:51 a.m. | Hanning Zhang, Shizhe Diao, Yong Lin, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang

cs.CL updates on arXiv.org arxiv.org

arXiv:2311.09677v2 Announce Type: replace
Abstract: Large language models (LLMs) have revolutionized numerous domains with their impressive performance but still face their challenges. A predominant issue is the propensity for these models to generate non-existent facts, a concern termed hallucination. Our research is motivated by the observation that previous instruction tuning methods force the model to complete a sentence no matter whether the model knows the knowledge or not. When the question is out of the parametric knowledge, it will try …

arxiv cs.cl language language models large language large language models type

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