2 citations · 2 across the 5 of their papers we have counts for
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cs.AI2025
LLM-Powered Preference Elicitation in Combinatorial Assignment
Ermis Soumalias, Yanchen Jiang, Kehang Zhu +3
We study the potential of large language models (LLMs) as proxies for humans to simplify preference elicitation (PE) in combinatorial assignment. While traditional PE methods rely…
cs.AI2024★ 2 cited
Scalable Mechanism Design for Multi-Agent Path Finding
Paul Friedrich, Yulun Zhang, Michael Curry +5
Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This p…