Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization

Large reasoning models (LRMs) improve language model capabilities by generating explicit thinking traces before final answers. In factuality-oriented question answering (QA), such thinking often improves overall performance by helping the model recover relevant knowledge and refine its answers. Howe...