In long agent executions, an early error can persist through later actions and checks, while evidence needed to trace its origin is dispersed across the history. Short histories offer limited tests of recovering error origins across substantial subsequent execution. We introduce LongRCA Bench: 1,140 complete failed tra...
Yun-Fei Zhang, Bo-Yu Feng, Changhua Pei et al.· 0 citations
Time series anomaly detection (TSAD) plays a pivotal role in domains ranging from industrial automation to IT operations and healthcare monitoring. Despite significant advances in point-wise outlier detection, real anomalies are often not obvious spikes. Instead, they frequently manifest as mechanism shifts, subtle cha...
Hang Cui, Ze-Xin Wang, Changhua Pei et al.· Proceedings of the 32nd ACM...· 0 citations
DUOTRACE follows a detect-before-attribute paradigm: it first detects anomalous executions and then supplies focused trajectory evidence to downstream LLM-based attribution methods, which improves agent-level and step-level attribution accuracy.
Jia-Yi Zhang, Ze-Xin Wang, DecisionMakingRon Sun et al.· 0 citations
This work introduces LongRCA Bench, comprising 1,140 failed trajectories across five domains without injected errors, and presents Root-Cause Trajectory Attribution (RCTA), a training-free method that retrieves candidate error steps from segment summaries and traces them to available earlier handoff instructions.
Yun-Fei Zhang, Bo-Yu Feng, Changhua Pei et al.· 1 citation
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