3 citations · 7 across the 10 of their papers we have counts for
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cs.MA2026
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference
Junzhi Li, Peng He, Qirui Ji +3
The performance of large language model (LLM)-based multi-agent systems (MAS) largely depends on effective communication topologies. Existing topology generation methods, however,…
cs.MA2025★ 3 cited
Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective
Chuxiong Sun, Peng He, Rui Wang +1
In this work, we introduce a novel perspective, i.e., dimensional analysis, to address the challenge of communication efficiency in Multi-Agent Reinforcement Learning (MARL). Our f…
cs.MA2024★ 2 cited
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference
Chuxiong Sun, Peng He, Qirui Ji +4
Communication is essential in coordinating the behaviors of multiple agents. However, existing methods primarily emphasize content, timing, and partners for information sharing, of…