Papers by Jiangwei Chen
Waterfall: Scalable Framework for Robust Text Watermarking and Provenance for LLMs (2024.emnlp-main)
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| Challenge: | Existing text watermarking methods are not robust enough against paraphrasing attacks . existing methods lack robustness to paraphrases and are not scalable to millions of users . |
| Approach: | They propose a training-free framework for robust and scalable text watermarking . they propose to use large language models as paraphrasers and a combination of techniques . |
| Outcome: | The proposed framework improves scalability, verifiability and computational efficiency compared to existing methods. |
Position Paper: Data-Centric AI in the Age of Large Language Models (2024.findings-emnlp)
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Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
| Challenge: | a paper proposes a data-centric perspective of AI research, focusing on large language models. |
| Approach: | They propose a data-centric viewpoint of AI research, focusing on large language models . they propose four scenarios centered around data, including data curation, attribution, knowledge transfer . |
| Outcome: | The proposed research focuses on large language models with data centric benchmarks . the proposed benchmarks can be used to develop new data curation methods . |