Understanding and Mitigating Premature Confidence for Better LLM Reasoning 事件

Understanding and Mitigating Premature Confidence for Better LLM Reasoning arXiv:2605.24396v1 Announce Type: new Abstract: Long chains of thought (CoT) from current language models frequently contain logical gaps and unjustified leaps, limiting the gains from additional test-time compute. Improving reasoning quality directly would require process reward models, but the step-level annotations needed to train them are expensive and scarce. We find such a signal in how the model's confidence evolv