A Watermark for Large Language Models
Kirchenbauer et al., 2023, A Watermark for Large Language Models (Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202)
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5 Private Watermarking
- How does a private watermark differ from a public one?The red lists depend on a secret key behind an API, so attackers don’t know which tokens to replace; but detection then requires the API, and access must be monitored so that an adversary can’t probe it with many slightly varied texts.
- Kirchenbauer et al., 2023, A Watermark for Large Language Models (Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202), §5
Source
- John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers and Tom Goldstein. 2023. A Watermark for Large Language Models. In Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202, pp. 17061–17084. https://proceedings.mlr.press/v202/kirchenbauer23a.html