CoRA: Confidence-Rationale Alignment for Reliable Chain-of-Thought Reasoning
Chain-of-thought (CoT) reasoning can improve LLM performance, but high answer confidence may be misleading when the accompanying CoT rationale is plausible yet incomplete or poorly supported. We study confidence--rationale alignment: whether a model's confidence in its committed answer is justified by its generated rationale. We introduce a GRPO-based reinforcement learning framework that jointly rewards answer correctness, committed-answer probability, and rubric-based rationale support, where the rubric assesses grounding, coherence, task match, and connection to the selected answer without revealing the gold answer to the judge. Across MedQA, MathQA, and OpenBookQA using three open-wei...
| Authors | Juming Xiong, Weixin Liu, Kevin Guo et al. |
|---|---|
| Primary category | cs.CL |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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