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cs.LG2026
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
Zhengzhao Ma, Xueru Wen, Boxi Cao +6
Reinforcement Learning from Verifiable Rewards (RLVR) significantly enhances large language models (LLMs) reasoning but severely suffers from calibration degeneration, where models…
cs.LG2024
Transferable Post-training via Inverse Value Learning
Xinyu Lu, Xueru Wen, Yaojie Lu +6
As post-training processes utilize increasingly large datasets and base models continue to grow in size, the computational demands and implementation challenges of existing algorit…
cs.LG2024
Rethinking Reward Model Evaluation: Are We Barking up the Wrong Tree?
Xueru Wen, Jie Lou, Yaojie Lu +7
Reward Models (RMs) are crucial for aligning language models with human preferences. Currently, the evaluation of RMs depends on measuring accuracy against a validation set of manu…