57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026U North Carolina at Chapel HillThe University of North CarolinaU Michigan - Ann ArborClinical NLP & EHRDistribution-First Framework for Learning Risk-Sensitive Individualized Treatment RulesZhen Fang, Guanting Chen, Yufeng LiuSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 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
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026The University of North CarolinaU Illinois at Urbana-ChampaignUSTCUNC-Chapel HillShanghai Jiao TongAgent benchmarks & environmentsSee, Read, Compare: Candidate-Aware Verification for Agent Test-Time ScalingXinyu Ye, Yongliang Wu, Xingyu Zhu, Peng Xia and 6 moreSydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet0/20 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: 0 of 20 reviewers recommend itlenient 0/5medium 0/10strict 0/5
80%Must read?Must readVote to see the scoreNeurIPS 2026UNC-Chapel HillU North Carolina at Chapel HillU ChicagoDepartment of Computer Science, U California, San DiegoRL for LLMsSkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement LearningSkillRL evolves agents via recursive skill-augmented reinforcement learning with automatic skill discovery and hierarchical library co-evolution, cutting token use while achieving state-of-the-art results across complex tasks.Peng Xia, Jianwen Chen, Hanyang Wang, Jiaqi Liu and 9 moreAtlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 75 on Hugging Face · Code ★ 998– 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 7/10strict 1/5