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provenance-tracking

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Inspired by dynamic taint tracking, PoisonSpot uses fine-grained training provenance tracker that: (1) tags & traces the impact of every single training sample on model updates, (2) probabilistically scores suspect samples based on their linage of impact on model weights, and (3) separates the clean from the poisonous before retraining a model.

  • Updated Jan 8, 2026
  • Python

Learning repository for testing ML workflow patterns through iterative experiments. Documents what works and what fails to enable research and citizen science initiatives.

  • Updated Jun 24, 2025
  • Jupyter Notebook

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