Streaming Hallucination Detection in Long Chain-of-Thought Reasoning

• URL: http://arxiv.org/abs/2601.02170v1
• Date: Mon, 05 Jan 2026 14:47:41 GMT
• Title: Streaming Hallucination Detection in Long Chain-of-Thought Reasoning
• Authors: Haolang Lu, Minghui Pan, Ripeng Li, Guoshun Nan, Jialin Zhuang, Zijie Zhao, Zhongxiang Sun, Kun Wang, Yang Liu,
• Abstract summary: hallucination in long CoT reasoning is better understood as an evolving latent state rather than a one-off erroneous event.<n>Our approach enables streaming hallucination detection in long CoT reasoning, providing real-time, interpretable evidence.
• Score: 12.874780445960424
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Long chain-of-thought (CoT) reasoning improves the performance of large language models, yet hallucinations in such settings often emerge subtly and propagate across reasoning steps. We suggest that hallucination in long CoT reasoning is better understood as an evolving latent state rather than a one-off erroneous event. Accordingly, we treat step-level hallucination judgments as local observations and introduce a cumulative prefix-level hallucination signal that tracks the global evolution of the reasoning state over the entire trajectory. Overall, our approach enables streaming hallucination detection in long CoT reasoning, providing real-time, interpretable evidence.

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