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Bergson: An Open Source Library for Data Attribution

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Computer Science > Machine Learning

arXiv:2606.11660 (cs)
[Submitted on 10 Jun 2026]

Title:Bergson: An Open Source Library for Data Attribution

View a PDF of the paper titled Bergson: An Open Source Library for Data Attribution, by Lucia Quirke and 8 other authors
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Abstract:Data attribution is a promising field in interpretability that aims to explain model behavior through the influence of its training data, with applications including debugging undesirable model behavior and training dataset curation. However, significant engineering effort is required to perform it at scale, and many cutting edge techniques lack open-source tooling and support. Bergson is an open source library that aims to enable faster progress in the field by providing a host of techniques that scale to very large language models and pre-training datasets. The library natively supports on-disk gradient stores and multi-node distributed training, and provides quality of life tools for researchers. Finally, we introduce the first open-source implementations of three leading data attribution methods: MAGIC, SOURCE, and TrackStar. The library is available at this https URL .
Subjects: Machine Learning (cs.LG)
Cite as: arXiv:2606.11660 [cs.LG]
  (or arXiv:2606.11660v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2606.11660
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Lucia Quirke [view email]
[v1] Wed, 10 Jun 2026 04:56:45 UTC (2,799 KB)
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