4 papers
ROAR: Benchmarking LMM Agents under Real-Time Constraints in Multiplayer Action-Shooter Games
Dawei Wang, Di Zhao, Jianran Yu +8
Large multimodal models (LMMs) are increasingly deployed as agents that perceive, reason, and act in interactive multi-agent environments. Yet most existing benchmarks for LMM-base…
Three Lessons from Citizen-Centric Participatory AI Design
Eike Schneiders, Sarah Kiden, Beining Zhang +5
This workshop paper examines challenges in designing agentic AI systems from a citizen-centric perspective. Drawing on three participatory workshops conducted in 2025 with members…
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz +83
Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…
Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning
Beining Zhang, Aditya Kapoor, Mingfei Sun
Multi-agent reinforcement learning (MARL) often relies on \emph{parameter sharing (PS)} to scale efficiently. However, purely shared policies can stifle each agent's unique special…