arXiv cs.CLPaper
Agent Error Dataset: Scaling 50,000 Error--Diagnosis Pairs for Failure Analysis and Error-Aware Post-Training
The real value is not the dataset itself but the methodology: they're showing how to systematically extract training signal from agent failures at scale. This matters because most teams treat failed rollouts as sunk cost. The five-stage pipeline from failure to diagnosis to validation is a template you can adapt. If you're building systems where agent failures are common, this signals that failure-driven learning is viable and worth instrumenting.