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Watermarking generative-AI systems, such as LLMs, has gained considerable interest, driven by their enhanced capabilities across a wide range of tasks.
Xtreme: A massively multilingual multi-task benchmark for evaluating cross-lingual generalization
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020 · 2003
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Multilingual translation with extensible multilingual pretraining and finetuning
Yuqing Tang, Chau Tran, Xian Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, and Angela Fan. 2020 · 2008
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Comet: A neural framework for mt evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022 · 2022
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Perplexity from plm is unreliable for evaluating text quality
Yequan Wang, Jiawen Deng, Aixin Sun, and Xuying Meng. 2022 · 2022
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Yu Fu, Deyi Xiong, and Yue Dong. 2023 · 2023
Cited alongside, same era.
Robust distortion-free watermarks for language models
Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, and Percy Liang. 2023 · 2023
Cited alongside, same era.
Improving the generation quality of watermarked large language models via word importance scoring
Yuhang Li, Yihan Wang, Zhouxing Shi, and Cho-Jui Hsieh. 2023 · 2023
Cited alongside, same era.
A semantic invariant robust watermark for large language models
Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, and Lijie Wen. 2023 · 2023
Cited alongside, same era.
Zero-shot nlg evaluation through pairware comparisons with llms
Zephyr: Direct distillation of lm alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, et al. 2023 · 2023
Later among the works it cites.
Towards codable text watermarking for large language models
Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin, Fandong Meng, Jie Zhou, and Xu Sun. 2023 · 2023
Later among the works it cites.
Provable robust watermarking for ai-generated text
Xuandong Zhao, Prabhanjan Ananth, Lei Li, and Yu-Xiang Wang. 2023 · 2023
Later among the works it cites.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2023 · 2023
Later among the works it cites.
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Adian Liusie, Potsawee Manakul, and Mark JF Gales. 2023 · 2023
Cited alongside, same era.
A robust semantics-based watermark for large language model against paraphrasing
Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, and Jiliang Tang. 2023 · 2023
Cited alongside, same era.
Necessary and sufficient watermark for large language models
Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, and Makoto Yamada. 2023 · 2023
Cited alongside, same era.
A watermark for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023a
Cited in the paper.
On the reliability of watermarks for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, and Tom Goldstein. 2023b
Cited in the paper.
Towards a unified multi-dimensional evaluator for text generation
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han. 2022 · 2038
Closest in time.
Robust multi-bit natural language watermarking through invariant features
KiYoon Yoo, Wonhyuk Ahn, Jiho Jang, and Nojun Kwak. 2023 · 2092
Closest in time.