SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation

• URL: http://arxiv.org/abs/2310.03991v2
• Date: Mon, 22 Apr 2024 04:29:38 GMT
• Title: SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation
• Authors: Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, Yulia Tsvetkov,
• Abstract summary: Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. We propose SemStamp, a robust sentence-level semantic watermarking algorithm based on locality-sensitive hashing (LSH) Experimental results show that our novel semantic watermark algorithm is not only more robust than the previous state-of-the-art method on both common and bigram paraphrase attacks, but also is better at preserving the quality of generation.
• Score: 72.10931780019297
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. To address this issue, we propose SemStamp, a robust sentence-level semantic watermarking algorithm based on locality-sensitive hashing (LSH), which partitions the semantic space of sentences. The algorithm encodes and LSH-hashes a candidate sentence generated by an LLM, and conducts sentence-level rejection sampling until the sampled sentence falls in watermarked partitions in the semantic embedding space. A margin-based constraint is used to enhance its robustness. To show the advantages of our algorithm, we propose a "bigram" paraphrase attack using the paraphrase that has the fewest bigram overlaps with the original sentence. This attack is shown to be effective against the existing token-level watermarking method. Experimental results show that our novel semantic watermark algorithm is not only more robust than the previous state-of-the-art method on both common and bigram paraphrase attacks, but also is better at preserving the quality of generation.

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