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The article explains a process for converting AI agent traces into a labeled training dataset, detailing steps like automatic capture, strategic sampling, and explicit labeling against criteria.
This paper introduces an enhanced C3LM model for single-step retrosynthesis using Top-K prompting and a larger training dataset, demonstrating competitive performance with conventional models on the URSA-expert-2026 benchmark.
OriginBlame is a record- and token-level data provenance system that propagates author identity through AI training data pipelines, enabling precise forget sets for machine unlearning. It eliminates over-deletion from dataset-level systems and improves unlearning effectiveness.