How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study-Reference-Cited by-同舟云学术

How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study

Published:2024-04-15 Issue: Volume: Page:
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Container-title:Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension
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Author:

Pepe Federica¹^ORCID,Nardone Vittoria²^ORCID,Mastropaolo Antonio³^ORCID,Bavota Gabriele³^ORCID,Canfora Gerardo¹^ORCID,Di Penta Massimiliano¹^ORCID

Affiliation:

1. University of Sannio, Benevento, Italy

2. University of Molise, Campobasso, Italy

3. Software Institute, Universita della Svizzera italiana (USI), Lugano, Switzerland

Funder

Italian Ministry of University and Research

European Research Council (ERC)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3643916.3644412

Reference55 articles.

1. 2023. Choose an open source license https://choosealicense.com.

2. 2023. Open Source Initiative https://opensource.org.

3. Avinash Bhat, Austin Coursey, Grace Hu, Sixian Li, Nadia Nahar, Shurui Zhou, Christian Kästner, and Jin L. C. Guo. 2023. Aspirations and Practice of ML Model Documentation: Moving the Needle with Nudging and Traceability. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023, Hamburg, Germany, April 23--28, 2023. ACM, 749:1--749:17.

4. BigScience. 2022. BigScience Large Open-science Open-access Multilingual Language Model https://huggingface.co/bigscience/bloom.

5. Sumon Biswas and Hridesh Rajan. 2022. Fairify: Fairness Verification of Neural Networks. arXiv preprint arXiv:2212.06140 (2022).

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