Paper 2023/1661 Original: eprint.iacr.org/2023/1661 ↗
Publicly-Detectable Watermarking for Language Models
Abstract
We present a publicly-detectable watermarking scheme for LMs: the detection algorithm contains no secret information, and it is executable by anyone. We embed a publicly-verifiable cryptographic signature into LM output using rejection sampling and prove that this produces unforgeable and distortion-free (i.e., undetectable without access to the public key) text output. We make use of error-correction to overcome periods of low entropy, a barrier for all prior watermarking schemes. We implement our scheme and find that our formal claims are met in practice.
Metadata
- Available format(s)
PDF- Category
- Applications
- Publication info
- Preprint.
- History
- 2025-01-04: last updated
- 2023-10-26: published
- Short URL
- https://ia.cr/2023/1661
- License
- https://creativecommons.org/licenses/by/4.0/
BibTeX
@misc{cryptoeprint:2023/1661,
author = {Jaiden Fairoze and Sanjam Garg and Somesh Jha and Saeed Mahloujifar and Mohammad Mahmoody and Mingyuan Wang},
title = {Publicly-Detectable Watermarking for Language Models},
howpublished = {Cryptology {ePrint} Archive, Paper 2023/1661},
year = {2023},
url = {https://eprint.iacr.org/2023/1661}
}