Reasoning Models Don’t Always Say What They Think
Chen et al., 2025, Reasoning Models Don’t Always Say What They Think (arXiv preprint arXiv:2505.05410)
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1 Introduction
- Why does chain-of-thought faithfulness matter for AI safety?Monitoring a model’s chain of thought could reveal its intentions and catch undesired behavior, but only if the chain of thought faithfully shows the factors that actually drove the answer. Training on user-facing responses could also teach models to hide reasoning.
- Chen et al., 2025, Reasoning Models Don’t Always Say What They Think (arXiv preprint arXiv:2505.05410), §1
Source
- Yanda Chen, Joe Benton, Ansh Radhakrishnan, Jonathan Uesato, Carson Denison, John Schulman, Arushi Somani, Peter Hase, Misha Wagner, Fabien Roger, Vlad Mikulik, Samuel R. Bowman, Jan Leike, Jared Kaplan and Ethan Perez. 2025. Reasoning Models Don’t Always Say What They Think. In arXiv preprint arXiv:2505.05410. https://arxiv.org/abs/2505.05410