LongRCA Bench: Root-Cause Localization in Long-Horizon Agent Trajectories
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 trajectories from five sources, all human-annotated for responsible roles and earliest decisive root-cause steps. Reference roots precede completion by a median of 48 recorded steps; 28.4% of trajectories contain over 100 subsequent steps. With DeepSeek-V4-Flash on the full benchmark, the strongest of five evaluated baselines achieves 13.2% exact root-step accuracy. We propose ...
| Authors | Yunfei Zhang, Boyu Feng, Changhua Pei et al. |
|---|---|
| Primary category | cs.AI |
| Published | 15 August 2026 |
| Last updated at source | 21 September 2026 |
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