57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026Hong Kong University of Science Hong Kong University of Science ZhejiangTianjinMontreal Institute for Learning RL for LLMsReformulate LLM Reinforcement Learning for Stable Training under Black-box DiscrepancyJiashun Liu, Runze Liu, Xu Wan, Jing Liang and 2 moreSydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet1/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 1 of 20 reviewers recommend itlenient 1/5medium 0/10strict 0/5
80%Must read?Must readVote to see the scoreNeurIPS 2026Kuaishou- 快手科技Hong Kong University of Science Alibaba groupHong Kong University of Science RL for LLMsStabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVRArcher applies entropy-aware dual-token constraints to RLVR, modulating optimization strengths across reasoning and knowledge tokens to improve mathematical and code performance.Jiakang Wang, Runze Liu, Fuzheng Zhang, Xiu Li and 3 moreSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 21 on Hugging Face · Code ★ 44– ReadersNo votes yet12/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 12 of 20 reviewers recommend itlenient 4/5medium 8/10strict 0/5
86%Must read?Must readVote to see the scoreNeurIPS 2026SpotlightFudanHong Kong University of Science Mila / Université de MontréalCity University of Hong KongHong Kong University of Science Deep RLLocal Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior TransitionsGaussian trust region reshaping replaces monotonic divergence penalties with bounded non-monotonic constraints, unlocking efficient behavior transitions in non-stationary reinforcement learning.Bingxu Liu, Jiashun Liu, Johan Obando Ceron, Hao Wang and 4 moreSydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet14/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 14 of 20 reviewers recommend itlenient 4/5medium 9/10strict 1/5