Good Papers

Showing papers from Southeast University, China Show all papers

57%Worth a look
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NeurIPS 2026Southeast山东建筑大学AdelaidenuaaSoutheast University, ChinaTool use & function calling

Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents

Yu Li, Zheng Zhang, Xin Liu, shengtian yang and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026SpotlightU MelbourneThe University of MelbourneSoutheast University, ChinaAmazonMonashVision-language models

Permute-then-Adapt: Weak-to-Strong Contrastive Image--Text Adaptation

Jinhao Li, Sarah Erfani, Lei Feng, Guangrui Li and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
71%Highly rated
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NeurIPS 2026SoutheastnuaaHuawei Technologies Ltd.Nanyang TechnologicalInstitute of automation, ChineseLLM agents & planning

PhGPO: Pheromone-Guided Policy Optimization for Long-Horizon Tool Planning

PhGPO 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 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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6/20 AI panelreviewers recommend it

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AI panel: 6 of 20 reviewers recommend it
lenient 4/5
medium 2/10
strict 0/5
83%Must read
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NeurIPS 2026Nanyang TechnologicalnuaaSoutheast University, ChinaKuaishou inc.Alibaba groupTool use & function calling

AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories

AgentBrew 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 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
74%Highly rated
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NeurIPS 2026Singapore ManagementU Electronic Science and TechnolSoutheast University, ChinaGraph neural networks

Understanding and Mitigating Under-Confidence in GNNs from the Final Layer

A unified framework reveals GNN under-confidence stems from final-layer weight decay and node distance, fixed by reducing decay and node-level calibration.

Jincheng Huang, Jie Xu, Ping Hu, Xiaoshuang Shi and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 0/5