57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026Southeast山东建筑大学AdelaidenuaaSoutheast University, ChinaTool use & function callingChoosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use AgentsYu Li, Zheng Zhang, Xin Liu, shengtian yang and 2 moreSydney Poster Session 5, Thu, Dec 10, 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
71%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026SoutheastnuaaHuawei Technologies Ltd.Nanyang TechnologicalInstitute of automation, ChineseLLM agents & planningPhGPO: Pheromone-Guided Policy Optimization for Long-Horizon Tool PlanningPhGPO learns reusable tool-transition patterns from past trajectories via pheromone guidance to improve long-horizon tool planning.Yu Li, Guangfeng Cai, shengtian yang, Han Luo and 4 moreSydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet6/20 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: 6 of 20 reviewers recommend itlenient 4/5medium 2/10strict 0/5
83%Must read?Must readVote to see the scoreNeurIPS 2026Nanyang TechnologicalnuaaSoutheast University, ChinaKuaishou inc.Alibaba groupTool use & function callingAgentBrew: Offline Tool-Use Agent Learning from Raw Real-World TrajectoriesAgentBrew learns tool-use policies offline from raw real-world trajectories via retrospective task inference and PMI-based credit assignment, improving Qwen3-32B by +8.7 accuracy over larger baselines.Zhiyi Lyu, Yewen Li, Longtao Zheng, shengtian yang and 6 moreSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet13/20 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: 13 of 20 reviewers recommend itlenient 5/5medium 7/10strict 1/5