Welcome</p>\n","updatedAt":"2026-05-13T04:28:02.429Z","author":{"_id":"67a4a26d5e65aa63c6d30e68","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/67a4a26d5e65aa63c6d30e68/GtodlJGw-_IL2DTXQTucz.jpeg","fullname":"Sicheng Feng","name":"FSCCS","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":12,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.3305741548538208},"editors":["FSCCS"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/67a4a26d5e65aa63c6d30e68/GtodlJGw-_IL2DTXQTucz.jpeg"],"reactions":[],"isReport":false}},{"id":"6a0482ad255af1730ef0211c","author":{"_id":"661ab1f1fa3b144a381fa454","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/661ab1f1fa3b144a381fa454/IlpZBb9NCjo7ntFwMIH53.png","fullname":"Urro","name":"urroxyz","type":"user","isPro":true,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":9,"isUserFollowing":false},"createdAt":"2026-05-13T13:54:53.000Z","type":"comment","data":{"edited":false,"hidden":false,"latest":{"raw":"Wow! Genius!\n\nText watermarking is important. I hope that stable research on it gets adopted so that communities can fight AI-generated spam.","html":"<p>Wow! Genius!</p>\n<p>Text watermarking is important. I hope that stable research on it gets adopted so that communities can fight AI-generated spam.</p>\n","updatedAt":"2026-05-13T13:54:53.237Z","author":{"_id":"661ab1f1fa3b144a381fa454","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/661ab1f1fa3b144a381fa454/IlpZBb9NCjo7ntFwMIH53.png","fullname":"Urro","name":"urroxyz","type":"user","isPro":true,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":9,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.9107217192649841},"editors":["urroxyz"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/661ab1f1fa3b144a381fa454/IlpZBb9NCjo7ntFwMIH53.png"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2605.10977","authors":[{"_id":"6a03f8f186b054ce2fa40eea","user":{"_id":"66def1e3ba8b9dac859dbd64","avatarUrl":"/avatars/84797ac61013046db3a495d5033f9d32.svg","isPro":false,"fullname":"Zhenxin Ai","user":"kunkk","type":"user","name":"kunkk"},"name":"Zhenxin Ai","status":"claimed_verified","statusLastChangedAt":"2026-05-13T07:43:53.369Z","hidden":false},{"_id":"6a03f8f186b054ce2fa40eeb","name":"Haiyun He","hidden":false}],"publishedAt":"2026-05-09T00:00:00.000Z","submittedOnDailyAt":"2026-05-13T00:00:00.000Z","title":"PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks","submittedOnDailyBy":{"_id":"67a4a26d5e65aa63c6d30e68","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/67a4a26d5e65aa63c6d30e68/GtodlJGw-_IL2DTXQTucz.jpeg","isPro":false,"fullname":"Sicheng Feng","user":"FSCCS","type":"user","name":"FSCCS"},"summary":"Watermarking for large language models (LLMs) is a promising approach for detecting LLM-generated text and enabling responsible deployment. However, existing watermarking methods are often vulnerable to semantic-invariant attacks, such as paraphrasing. We propose PASA, a principled, robust, and distortion-free watermarking algorithm that embeds and detects a watermark at the semantic level. PASA operates on semantic clusters in a latent embedding space and constructs a distributional dependency between token and auxiliary sequences via shared randomness synchronized by a secret key and semantic history. This design is grounded in our theoretical framework that characterizes a jointly optimal embedding-detection pair, achieving the fundamental trade-offs among detection accuracy, robustness, and distortion. Evaluations across multiple LLMs and semantic-invariant attacks demonstrate that PASA remains robust even under strong paraphrasing attacks while preserving high text quality, outperforming standard vocabulary-space baselines. Ablation studies further validate the effectiveness of our hyperparameter choices. 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PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks
Abstract
PASA is a robust watermarking algorithm for large language models that operates at the semantic level using latent embedding spaces and shared randomness for secure text detection.
AI-generated summary
Watermarking for large language models (LLMs) is a promising approach for detecting LLM-generated text and enabling responsible deployment. However, existing watermarking methods are often vulnerable to semantic-invariant attacks, such as paraphrasing. We propose PASA, a principled, robust, and distortion-free watermarking algorithm that embeds and detects a watermark at the semantic level. PASA operates on semantic clusters in a latent embedding space and constructs a distributional dependency between token and auxiliary sequences via shared randomness synchronized by a secret key and semantic history. This design is grounded in our theoretical framework that characterizes a jointly optimal embedding-detection pair, achieving the fundamental trade-offs among detection accuracy, robustness, and distortion. Evaluations across multiple LLMs and semantic-invariant attacks demonstrate that PASA remains robust even under strong paraphrasing attacks while preserving high text quality, outperforming standard vocabulary-space baselines. Ablation studies further validate the effectiveness of our hyperparameter choices. Webpage: https://ai-kunkun.github.io/PASA_page/.
Community
Wow! Genius!
Text watermarking is important. I hope that stable research on it gets adopted so that communities can fight AI-generated spam.
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Cite arxiv.org/abs/2605.10977 in a model README.md to link it from this page.
Cite arxiv.org/abs/2605.10977 in a dataset README.md to link it from this page.
Cite arxiv.org/abs/2605.10977 in a Space README.md to link it from this page.
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