SOURCE-LINKED INTELLIGENCE

OpenMAS-GCom. A Diagnostic Benchmark for Graph-enhanced Multi-Agent Systems

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Graph-enhanced multi-agent systems (G-MAS) coordinate large language model agents through communication graphs and role assignments, which determine how agents exchange information and divide responsibilities. However, final-score comparisons across systems combine differences in models, communication patterns, roles, and computation costs, making performance differences difficult to attribute to specific communication structures, role assignments, and information flows. To address this evaluation attribution problem, we introduce OpenMAS-GCom, a benchmark for diagnosing how these components a

Read original source ↗ Open in workspace

recordType

paper

region

Global