Purdue's AutoTraceGT automates grounded theory coding to analyze agent behavior at scale
Purdue · hf · 2026-09-04
Purdue released AutoTraceGT on Hugging Face, automating grounded-theory coding over agent trajectories to enable large-scale behavior analysis.
- Builds task-specific behavioral taxonomies from raw agent traces via automated open coding.
- Recovers human-annotated failure modes and extends them with new categories humans missed.
- The resulting taxonomies feed downstream prediction tasks, offering a scalable approach to agent evaluation and failure-mode research.
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