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Oct 12 · Monday

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LLM applications8AI Agent6Multi-agent systems1

Attack surface / entry point

User input5Web pages and interfaces0Documents and messages1Inter-agent messages3

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Guardrails and judges1
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System type：Multi-agent systemsAttack surface / entry point：Web pages and interfacesAttack surface / entry point：Documents and messagesSystem component：Guardrails and judgesClear all

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  1. DefensesarXiv 2603.04474

    From Spark to Wildfire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration

    Proposing a lineage-graph governance layer to suppress error cascades in multi-agent collaboration

    arXiv
    2603.04474
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    AbstractA single seed can solidify into a false consensus along a fixed collaboration graph.

    The authors turn "small errors becoming collective false consensus" in LLM-MAS into a measurable propagation on a graph, and use a plug-in that only changes messages, not topology, to reduce the final infection.

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