Preprint
Aug 2026
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference
E2-Explainer is proposed, a model-agnostic framework for providing interpretable explanations of communication topologies produced by arbitrary topology generators that identifies compact communication subgraphs supported by edge-level evidence of task preservation.
Junzhi Li, Peng He, Qirui Ji et al.
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