ProtocolBench: Which LLM MultiAgent Protocol to Choose?
Hongyi Du, Jiaqi Su, Jisen Li, Lijie Ding, Yingxuan Yang, Peixuan Han, Robert Tang, Kunlun Zhu, Jiaxuan You
摘要
As large-scale multi-agent systems evolve, the communication protocol layer has become a critical yet under-evaluated factor shaping performance and reliability. Despite the existence of diverse protocols (A2A, ACP, ANP, Agora, etc.), the selection of them is often intuition-driven and lacks standardized guidance. We introduce ProtocolBench, a benchmark that systematically compares agent protocols along four measurable axes: task success, end-to-end latency, message or byte overhead, and robustness under failures. On ProtocolBench, the choice of protocol significantly influences system behavior. In the Streaming Queue scenario, overall completion time varies by up to 36.5% across protocols, and mean end-to-end latency differs by 3.48 s. Under Fail-Storm Recovery, resilience also differs consistently across protocols. Beyond evaluation, we present ProtocolRouter, a lightweight constraint-aware protocol router that selects per-scenario (or per-module) protocols from requirement and runtime signals. ProtocolRouter reduces Fail-Storm recovery time by up to 18.1% versus the best single-protocol baseline and achieves scenario-specific gains such as higher success in GAIA, while exposing trade-offs across other metrics. We also release ProtocolRouterBench to standardize constrained protocol-selection evaluation and improve reliability at scale.
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它引用的顶会 Paper4
- GAIA: a benchmark for General AI AssistantsGrégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun 等ICLR 2024 · 被引用 716 次
- OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task AutomationMengkang Hu, Yuhang Zhou, Wendong Fan, Yuzhou Nie 等NeurIPS 2025 · 被引用 158 次
- MultiAgentBench : Evaluating the Collaboration and Competition of LLM agentsKunlun Zhu, Hongyi Du, Zhaochen Hong, Xiaocheng Yang 等ACL 2025 · 被引用 97 次
- Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative IntelligenceWeize Chen, Ziming You, Ran Li, Yitong Guan 等ICLR 2025 · 被引用 3 次
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