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cs.CL2024
FactAlign: Long-form Factuality Alignment of Large Language Models
Chao-Wei Huang, Yun-Nung Chen
Large language models have demonstrated significant potential as the next-generation information access engines. However, their reliability is hindered by issues of hallucination a…
cs.CL2024
LLMs are Biased Evaluators But Not Biased for Retrieval Augmented Generation
Yen-Shan Chen, Jing Jin, Peng-Ting Kuo +2
Recent studies have demonstrated that large language models (LLMs) exhibit significant biases in evaluation tasks, particularly in preferentially rating and favoring self-generated…