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With the rise of large language models (LLMs) and concerns about potential misuse, watermarks for generative LLMs have recently attracted much attention.
Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
Venugopal, A., Uszkoreit, J., Talbot, D., Och, F., and Ganitkevitch, J · 2011
Earlier work this paper cites.
Neural Linguistic Steganography
Ziegler, Z., Deng, Y., and Rush, A · 2019
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2020
Earlier work this paper cites.
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
Abdelnabi, S. and Fritz, M · 2021
Earlier work this paper cites.
My AI Safety Lecture for UT Effective Altruism, 2022
Aaronson, S · 2022
Earlier work this paper cites.
On pushing DeepFake Tweet Detection capabilities to the limits
Gambini, M., Fagni, T., Falchi, F., and Tesconi, M · 2022
Earlier work this paper cites.
AI-generated answers temporarily banned on coding Q&A site Stack Overflow, 2022
Vincent, J · 2022
Earlier work this paper cites.
OPT: Open Pre-trained Transformer Language Models
Zhang, S., Roller, S., Goyal, N., Artetxe, M., Chen, M., Chen, S., Dewan, C., Diab, M., Li, X., Lin, X. V., Mihaylov, T., Ott, M., Shleifer, S., Shuster, K., Simig, D., Koura, P. S., Sridhar, A., Wang, T., and Zettlemoyer, L · 2022
Earlier work this paper cites.
Performance Trade-offs of Watermarking Large Language Models
Ajith, A., Singh, S., and Pruthi, D · 2023
Earlier work this paper cites.
OpenAI, Google, others pledge to watermark AI content for safety, White House says, 2023
Bartz, D. and Hu, K · 2023
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X-Mark: Towards Lossless Watermarking Through Lexical Redundancy
Chen, L., Bian, Y., Deng, Y., Li, S., Wu, B., Zhao, P., and Wong, K.-f · 2023
Earlier work this paper cites.
Undetectable Watermarks for Language Models
Christ, M., Gunn, S., and Zamir, O · 2023
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COSYWA: Enhancing Semantic Integrity in Watermarking Natural Language Generation
Fang, J., Tan, Z., and Shi, X · 2023
Earlier work this paper cites.
Fu, Y., Xiong, D., and Dong, Y · 2023
Cited alongside, same era.
Goldstein, J. A., Sastry, G., Musser, M., DiResta, R., Gentzel, M., and Sedova, K · 2023
Cited alongside, same era.
On the Learnability of Watermarks for Language Models
Gu, C., Li, X. L., Liang, P., and Hashimoto, T · 2023
Cited alongside, same era.
Unbiased Watermark for Large Language Models
Hu, Z., Chen, L., Wu, X., Wu, Y., Zhang, H., and Huang, H · 2023
Cited alongside, same era.
Natural language watermarking via paraphraser-based lexical substitution
Qiang, J., Zhu, S., Li, Y., Zhu, Y., Yuan, Y., and Wu, X · 2023
Closest in time.
Risks and Benefits of Large Language Models for the Environment
Rillig, M. C., Ågerstrand, M., Bi, M., Gould, K. A., and Sauerland, U · 2023
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Can AI-Generated Text be Reliably Detected?
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., and Feizi, S · 2023
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Red Teaming Language Model Detectors with Language Models
Shi, Z., Wang, Y., Yin, F., Chen, X., Chang, K.-W., and Hsieh, C.-J · 2023
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Baselines for Identifying Watermarked Large Language Models
Tang, L., Uberti, G., and Shlomi, T · 2023
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Jiang, Z., Zhang, J., and Gong, N. Z · 2023
Cited alongside, same era.
Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense
Krishna, K., Song, Y., Karpinska, M., Wieting, J., and Iyyer, M · 2023
Cited alongside, same era.
Robust Distortion-free Watermarks for Language Models
Kuditipudi, R., Thickstun, J., Hashimoto, T., and Liang, P · 2023
Cited alongside, same era.
Who Wrote this Code? Watermarking for Code Generation
Lee, T., Hong, S., Ahn, J., Hong, I., Lee, H., Yun, S., Shin, J., and Kim, G · 2023
Cited alongside, same era.
ChatGPT and large language models in academia: opportunities and challenges
Meyer, J. G., Urbanowicz, R. J., Martin, P. C. N., O’Connor, K., Li, R., Peng, P.-C., Bright, T. J., Tatonetti, N., Won, K. J., Gonzalez-Hernandez, G., and Moore, J. H · 2023
Cited alongside, same era.
Large language models challenge the future of higher education
Milano, S., McGrane, J. A., and Leonelli, S · 2023
Cited alongside, same era.
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Mitchell, E., Lee, Y., Khazatsky, A., Manning, C. D., and Finn, C · 2023
Cited alongside, same era.
Munyer, T. and Zhong, X · 2023
Cited alongside, same era.
WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models
Tu, S., Sun, Y., Bai, Y., Yu, J., Hou, L., and Li, J · 2023
Closest in time.
Towards Codable Text Watermarking for Large Language Models
Wang, L., Yang, W., Chen, D., Zhou, H., Lin, Y., Meng, F., Zhou, J., and Sun, X · 2023
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DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models
Wu, Y., Hu, Z., Zhang, H., and Huang, H · 2023
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Watermarking Text Generated by Black-Box Language Models
Yang, X., Chen, K., Zhang, W., Liu, C., Qi, Y., Zhang, J., Fang, H., and Yu, N · 2023
Closest in time.
Robust Multi-bit Natural Language Watermarking through Invariant Features
Yoo, K., Ahn, W., Jang, J., and Kwak, N · 2023
Closest in time.
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Zhang, H., Edelman, B. L., Francati, D., Venturi, D., Ateniese, G., and Barak, B · 2023
Closest in time.
Provable Robust Watermarking for AI-Generated Text
Zhao, X., Ananth, P., Li, L., and Wang, Y.-X · 2023
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