GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems explores An open-source framework for benchmarking anomaly detection defenses in LLM multi-agent systems, generating synthetic data and evaluating defense models.. Commercial viability score: 7/10 in LLM Multi-Agent Systems.
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Canonical ID gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systems | Route /paper/gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systems
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curl https://sciencetostartup.com/api/v1/agent-handoff/paper/gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systemsMCP example
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/buildability/gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systems
Subject: GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems
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Dimensions overall score 7.0
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Receipt path
/buildability/gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systems
Paper ref
gammaf-a-common-framework-for-graph-based-anomaly-monitoring-benchmarking-in-llm-multi-agent-systems
arXiv id
2604.24477
Generated at
2026-04-28T15:17:49.879Z
Evidence freshness
fresh
Last verification
2026-04-28T15:17:49.879Z
Sources
3
References
0
Coverage
50%
Lineage hash
e4870bf2dff28c1958960ec0dff2da743c549760dbd0fe8a75fa2509e82bd628
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references
This equation captures one of the core mathematical components of the system. The inference data is collected as an attributed graph G = (V, E), where each node v ∈V represents an agent and each
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This equation captures one of the core mathematical components of the system. edge e ∈E denotes a communication channel. Because employing raw text directly as node attributes is not ideal, the
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This equation captures one of the core mathematical components of the system. tasks achieve consensus immediately after the first round. These bounds are defined as W = N × (Qg + Qe) × r and
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