#failure-analysis2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago9

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From Flat Logs to Causal Graphs: Hierarchical Failure Attribution for LLM-based Multi-Agent Systems

Researchers introduce CHIEF, a new framework that improves failure analysis in LLM-powered multi-agent systems by transforming execution logs into hierarchical causal graphs. The system uses oracle-guided backtracking and counterfactual attribution to better identify root causes of failures, outperforming existing methods on benchmark tests.

AINeutralarXiv – CS AI · 4h ago5

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Demystifying the Lifecycle of Failures in Platform-Orchestrated Agentic Workflows

Researchers present AgentFail, a dataset of 307 real-world failure cases from agentic workflow platforms, analyzing how multi-agent AI systems fail and can be repaired. The study reveals that failures in these low-code orchestrated AI workflows propagate differently than traditional software, making them harder to diagnose and fix.