57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026OralShanghai Jiao TongShanghai JiaotongHuawei Technologies Ltd.Shanghai Jiao Tong UnviersityMulti-agent LLM systemsSMART: Scalable Multi-Agent Role-conditioned Teaming via LLM-free Tree SearchRunzhe Zhang, Ning Li, Xingshan Zeng, Letian Chen and 4 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
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026Shanghai JiaotongTencent Technology (shanghai) CoShanghai Jiao TongTencentTencent YouTu LabRL for LLMsGrounding Agent Reasoning with Structured Process Supervision for Multi-turn Reinforcement LearningRenting Rui, Yulei Qin, Weiwen Liu, Yunjia Xi and 4 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
88%Must read?Must readVote to see the scoreNeurIPS 2026Shanghai JiaotongTencentHuawei Technologies Ltd.The Hong Kong University of ScieU Edinburgh, University of EdinbHallucination & factualityBALTO: Balanced Token-Level Policy Optimization for Hallucination MitigationBALTO applies balanced token-level credit assignment to mitigate LLM hallucinations by redistributing probability from unsupported to faithful content, outperforming response-level methods on faithfulness benchmarks.Ning Li, Zixuan Guo, Yan Xu, Wenbo Fei and 6 moreSydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet15/20 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: 15 of 20 reviewers recommend itlenient 5/5medium 9/10strict 1/5