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cs.CL2026
When Words Fall Short: Iterative Synergy Between Verbalized Reasoning and Hidden Features for LLM Confidence Estimation
Yekun Xu, Ante Wang, Jingyi Ren +3
Confidence estimation is crucial for developing trustworthy large language models (LLMs), with most methods following estimator-based or verbalization-based paradigms. While recent…
cs.CL2026
Don't Wait to Reply: Towards Responsive yet Thoughtful Dialogue through Proactive Thinking
Ante Wang, Jiaqi Fu, Xuanyi Chen +4
Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks. However, its reactive nature, where reasoning is passively triggered only upo…
cs.LG2026
Enhancing LLM Metacognition via Cognitive Pairwise Training
Weitao Li, Hao Zhou, Xuanyu Lei +11
Reinforcement learning with verifiable rewards (RLVR) has become central to LLM reasoning, but its outcome-level rewards can make models more willing to give confident answers when…