🔗 Who cites «Provable Robust Watermarking for AI-Generated Text»

83 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← back to «Provable Robust Watermarking for AI-Generated Text»

1. Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defenseConference on Neural Information Processing Systems (NeurIPS)Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al.2023 · 310 citations
2. Can AI-Generated Text be Reliably Detected?arXiv:2303.11156Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.2023 · 306 citations
3. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
4. Ghostbuster: Detecting Text Ghostwritten by Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Vivek Verma, Eve Fleisig, Nicholas Tomlin, et al.2024 · 122 citations
5. Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer ReviewsarXiv:2403.07183Weixin Liang, Zachary Izzo, Yaohui Zhang, et al.2024 · 119 citations
6. Who Wrote this Code? Watermarking for Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Taehyun Lee, Seokhee Hong, Jaewoo Ahn, et al.2024 · 103 citations
7. Mapping the Increasing Use of LLMs in Scientific PapersarXiv:2404.01268Weixin Liang, Yaohui Zhang, Zhengxuan Wu, et al.2024 · 89 citations
8. Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent SystemAnnual Meeting of the Association for Computational Linguistics (ACL)Haoyang Su, Renqi Chen, Shixiang Tang, et al.2025 · 40 citations
9. MorphMark: Flexible Adaptive Watermarking for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zongqi Wang, Tianle Gu, Baoyuan Wu, et al.2025 · 12 citations
10. Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?Annual Meeting of the Association for Computational Linguistics (ACL)Leyi Pan, Aiwei Liu, Shiyu Huang, et al.2025 · 11 citations
11. Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical AdoptionFindings of the Association for Computational LinguisticsYepeng Liu, Xuandong Zhao, Dawn Song, et al.2026 · 2 citations
12. Measuring Human Contribution in AI-Assisted Content GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Yueqi Xie, Tao Qi, Jingwei Yi, et al.2026 · 1 citation
13. Topic-Based Watermarks for Large Language ModelsFindings of the Association for Computational LinguisticsAlexander Nemecek, Yuzhou Jiang, Erman Ayday2026 · 1 citation
14. Beyond A Fixed Seal: Adaptive Stealing Watermark in Large Language ModelsFindings of the Association for Computational LinguisticsShuhao Zhang, Yuli Chen, Jiale Han, et al.2026
15. Knowledge-Infused Multi-Bit Watermarking for RAG Knowledge BasesFindings of the Association for Computational LinguisticsKe Yang, Shuguang Yuan, Jing Yu, et al.2026
16. Protecting Language Models Against Unauthorized Distillation through Trace RewritingAnnual Meeting of the Association for Computational Linguistics (ACL)Xinhang Ma, William Yeoh, Ning Zhang, et al.2026
17. ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Peizhuo Lv, Ruihua Zhou, Yunpeng Li, et al.2026
18. Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party FrameworkFindings of the Association for Computational LinguisticsZhuoshang Wang, Yubing Ren, Yanan Cao, et al.2026
19. SWAN: Semantic Watermarking with Abstract Meaning RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Ziping Ye, Gourab Dey, Christos Christodoulopoulos, et al.2026
20. The Challenge of Identifying the Origin of Black-Box Large Language ModelsWorkshop on Privacy in Natural Language ProcessingZiqing Yang, Yixin Wu, Yun Shen, et al.2026
21. You Can Have a Second Chance: Unbiased and Multi-bit Watermarking for Diffusion Language Models with Regret-based RemaskingAnnual Meeting of the Association for Computational Linguistics (ACL)Ke Yang, Dongyang Liang, Jing Yu, et al.2026

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