Unverified50% confidenceFactExact time
Institutions such as OpenAI have repeatedly emphasized the risks of over-optimizing chain-of-thought in related research.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
8/31/2026
First Seen
Valid until: 11/29/2026
Sources
Related Entities
Related Claims
UnverifiedOpenAI研究员早在2021年发表论文指出过度优化奖励信号的风险77% similarUnverified安全研究者将系统行动能力远超其安全判断能力的潜在风险称为能力越界（Capability Overhang）68% similarVerifiedExcessive safety fine-tuning can cause models to over-refuse, undermining their practical utility.66% similarVerifiedSome models carry the risk of over-optimization toward test sets, causing leaderboard scores to deviate from real-world performance (benchmark saturation).65% similarUnverifiedOver-refusal strategies reduce risk but harm model utility, especially in scenarios such as professional development and security research that require touching sensitive boundaries.64% similar
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