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arXiv · 2310.18491

Publicly-Detectable Watermarking for Language Models

Jaiden Fairoze·Sanjam Garg·Somesh Jha·Saeed Mahloujifar·Mohammad Mahmoody·Mingyuan Wang
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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.

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Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang. 2023-10-27. Publicly-Detectable Watermarking for Language Models. https://arxiv.org/abs/2310.18491

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