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Showing papers from University of Nebraska-Lincoln Show all papers

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NeurIPS 2026SoutheastU Nebraska-LincolnSoutheast University, TsinghuaFinance & economics

Learning Menu-Based Mechanisms for Truthful Budget-Feasible Procurement

Peng Chen, Xiang Liu, Hau Chan, Yan Lyu and 2 more

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

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NeurIPS 2026U Nebraska-LincolnU Nebraska, LincolnU GeorgiaOberlin CollegeMulti-agent RL

PLATO: Pointer Learner for Agent and Task Openness

PLATO uses a pointer-network actor and GNN critic to handle open multi-agent reinforcement learning with unbounded agent and task spaces, achieving strong zero-shot generalization.

Alireza Saleh Abadi, Leen-Kiat Soh, Daniel A Redder, Adam Eck and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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lenient 5/5
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strict 0/5