Towards Mitigating Deceptive Safety Alignment in Large Reasoning Models
Large Reasoning Models (LRMs) are commonly trained with reinforcement learning (RL) to improve their generation of chain-of-thought (CoT) reasoning before producing final answers. However, RL rewards are typically assigned based on final answers, providing little or no direct supervision over intermediate reasoning. Th...
Xiang-Yu Zhou, S. Z. Zade, Rafi Ibn Sultan et al.
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