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cs.AI2026
Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
Zhanming Shen, Jintao Tong, Shaotian Yan +9
On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference solutions provides token-lev…
cs.AI2026
Momentum for Reasoning: Dense Intrinsic Signals in Policy Optimization
Hao Chen, Zhanming Shen, Liyao Li +8
Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for eliciting long-chain reasoning in large language models. However, existing methods base…
cs.AI2025
Reinforcement Learning with Rubric Anchors
Zenan Huang, Yihong Zhuang, Guoshan Lu +18
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a powerful paradigm for enhancing Large Language Models (LLMs), exemplified by the success of OpenAI's o-series…