ROAR: Benchmarking LMM Agents under Real-Time Constraints in Multiplayer Action-Shooter Games
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-based agents in multi-agent settings remain turn-based: the environment and other agents pause while an agent performs inference. Such protocols...