BRIDGE: Selective Boundary Repair with Dependency Graph Evidence in Multi-Agent Systems

Key points

• Multi-agent collaboration has emerged as a critical paradigm for tackling complex, long-horizon tasks; however, while coordination protocols continue to advance, systemic failures at the inter-agent collaboration interface remain a pervasive bottleneck.1
• In collaborative workflows, systems frequently suffer from broken handoffs---where critical task context is omitted, misrouted, or ignored despite each agent emitting locally plausible responses.1
• Central to \method is an integrated fault-attribution and calibration pipeline, \dataset, which decouples execution dependencies and injects counterfactual handoff perturbations to provide empirical supervision for runtime intervention.1
• Leveraging this diagnostic foundation, \method dynamically compiles observable interaction traces into a provenance graph to pinpoint unresolved dependencies, without accessing private agent states.1

Sources (1)

• [1]BRIDGE: Selective Boundary Repair with Dependency Graph Evidence in Multi-Agent Systems
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 06:31 AM

  To address this challenge, we present \method, a verifiable runtime control framework that treats handoff repair as selective intervention over explicit dependency graphs.

  Multi-agent collaboration has emerged as a critical paradigm for tackling complex, long-horizon tasks; however, while coordination protocols continue to advance, systemic failures at the inter-agent collaboration interface remain a pervasive bottleneck.

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