Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

arXiv
Trackbacks

Trackbacks indicate external web sites that link to articles in arXiv.org. Trackbacks do not reflect the opinion of arXiv.org and may not reflect the opinions of that article's authors.

Trackback guide

By sending a trackback, you can notify arXiv.org that you have created a web page that references a paper. Popular blogging software supports trackback: you can send us a trackback about this paper by giving your software the following trackback URL:

https://arxiv.org/trackback/{arXiv_id}

Some blogging software supports trackback autodiscovery -- in this case, your software will automatically send a trackback as soon as your create a link to our abstract page. See our trackback help page for more information.

Trackbacks for 2107.06499

Provable Copyright Protection for Generative Models

[ Windows On Theory@ INVALID-URL ] trackback posted Wed, 22 Feb 2023 02:22:01 UTC

Click to view metadata for 2107.06499

[Submitted on 14 Jul 2021 (v1), last revised 24 Mar 2022 (this version, v2)]

Title:Deduplicating Training Data Makes Language Models Better

Authors:Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini
Abstract:
Comments: Accepted to ACL 2022
Subjects: Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2107.06499 [cs.CL]
  (or arXiv:2107.06499v2 [cs.CL] for this version)