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ICLR 2026Blog Track PosterAccept (Poster)

Is the evidence in 'Language Models Learn to Mislead Humans via RLHF' valid?

Aaryan Chandna, Lukas Fluri, Micah Carroll

University of California, Berkeley · ETH Zurich · University of California Berkeley

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摘要

*Language Models Learn to Mislead Humans Via RLHF* (published at ICLR 2025) argues that RLHF can unintentionally train models to mislead humans – a phenomenon termed Unintentional-SOPHISTRY. However, our review of the paper's code and experiments suggests that a significant portion of their empirical findings may be due largely to major bugs that make the RLHF setup both unrealistic and highly prone to reward hacking. In addition to high-level claims, we correct these issues for one of their experiments, and fail to find evidence that supports the original paper's claims.