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Bergson library released for open-source data attribution in ML

By PulseAugur Editorial · [1 sources] ·

A new open-source library called Bergson has been released to facilitate data attribution in machine learning. This library aims to simplify the process of explaining model behavior by tracing its influence back to the training data. Bergson offers scalable techniques for large language models and pre-training datasets, including support for distributed training and on-disk gradient stores. It also provides open-source implementations of three prominent data attribution methods: MAGIC, SOURCE, and TrackStar. AI

IMPACT Enables researchers to more easily debug models and curate training datasets by providing scalable tools for data attribution.

RANK_REASON This is a research paper introducing an open-source library for data attribution in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Bergson library released for open-source data attribution in ML

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This is a research paper introducing an open-source library for data attribution in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Lucia Quirke, Louis Jaburi, David Johnston, William Z. Li, Gon\c{c}alo Paulo, Guillaume Martres, Girish Gupta, Stella Biderman, Nora Belrose ·

    Bergson: An Open Source Library for Data Attribution

    arXiv:2606.11660v1 Announce Type: new 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…

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