most citedChain-of-Thought Prompting Obscures Hallucination Cues in Large Language Models: An Empirical Evaluation

2 citations · 2 across the 2 of their papers we have counts for

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cs.CL2025★ 2 cited

Chain-of-Thought Prompting Obscures Hallucination Cues in Large Language Models: An Empirical Evaluation

Jiahao Cheng, Tiancheng Su, Jia Yuan +5

Large Language Models (LLMs) often exhibit \textit{hallucinations}, generating factually incorrect or semantically irrelevant content in response to prompts. Chain-of-Thought (CoT)…

cs.CL2025

Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection

Kedi Chen, Qin Chen, Jie Zhou +7

Large Language Models (LLMs) are prone to hallucination with non-factual or unfaithful statements, which undermines the applications in real-world scenarios. Recent researches focu…