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News/Improving LLM Interpretability with User-Centric Chain-of-Thought Reasoning
arxiv
PublishedAugust 28, 2026 at 4:00 AM
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Improving LLM Interpretability with User-Centric Chain-of-Thought Reasoning

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arXiv:2608.26166v1 Announce Type: cross Abstract: Advancing reasoning capabilities allow large language models (LLMs) to tackle increasingly complex problems, while reasoning traces - intermediate steps toward solutions - open up high-stakes applications by enabling human inspection of AI decision-m

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