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Jie Ren 任杰
I am a fourth-year Ph.D. student of Department of Computer Science and Engineering at Michigan State University, advised by Professor Jiliang Tang in Data Science and Engineering Lab. Before joining DSE, I was an algorithm engineer in Search Strategy Department, Baidu Inc. I got my bachelor degree from Tsinghua University.
My research interests focus on Trustworthy AI, especially on the data and model copyright protection in Generative AI.
Email: renjie3 [at] msu.edu
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LinkedIn
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News
[Nov 2024] One paper accepted by TMLR!
[Sep 2024] One paper accepted by EMNLP!
[Aug 2024] I will start my internship at Amazon in Fall 2024!
[Jul 2024] My submission is accepted by ECAI 2024 Doctoral Consortium!
[Jul 2024] One paper accepted by ECCV!
[May 2024] Two papers accepted by ACL!
[Mar 2024] I will start my internship at Sony AI in March.
[Mar 2024] Our paper, A Robust Semantics-based Watermark for Large Language Model against Paraphrasing, is accepted by NAACL Findings.
[Feb 2024] The preprint of our survey, Copyright Protection in Generative AI: A Technical Perspective, is released.
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Preprints (* equal contribution)
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models
Jie Ren,
Kangrui Chen,
Chen Chen,
Vikash Sehwag,
Yue Xing,
Jiliang Tang,
Lingjuan Lyu
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations
Jie Ren,
Yingqian Cui,
Chen Chen,
Vikash Sehwag,
Yue Xing,
Jiliang Tang,
Lingjuan Lyu
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models
Jie Ren*,
Kangrui Chen*,
Yingqian Cui,
Shenglai Zeng,
Hui Liu,
Yue Xing,
Jiliang Tang,
Lingjuan Lyu
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
Shenglai Zeng,
Jiankun Zhang,
Pengfei He,
Jie Ren,
Tianqi Zheng,
Hanqing Lu,
Han Xu,
Hui Liu,
Yue Xing,
Jiliang Tang
Copyright Protection in Generative AI: A Technical Perspective
Jie Ren,
Han Xu,
Pengfei He,
Yingqian Cui,
Shenglai Zeng,
Jiankun Zhang,
Hongzhi Wen,
Jiayuan Ding,
Pei Huang,
Lingjuan Lyu,
Hui Liu,
Yi Chang,
Jiliang Tang
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
Yingqian Cui,
Jie Ren,
Yuping Lin,
Han Xu,
Pengfei He,
Yue Xing,
Wenqi Fan,
Hui Liu,
Jiliang Tang
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Yuxuan Wan,
Han Xu,
Xiaorui Liu,
Jie Ren,
Wenqi Fan,
Jiliang Tang
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Publications (* equal contribution)
Stealthy Backdoor Attack via Confidence-driven Sampling
Pengfei He,
Han Xu,
Jie Ren,
Yingqian Cui,
Shenglai Zeng,
Yue Xing,
Jiliang Tang,
Makoto Yamada,
Mohammad Sabokrou
Transactions on Machine Learning Research (TMLR), 2024.
On the Generalization of Training-based ChatGPT Detection Methods
Han Xu,
Jie Ren,
Pengfei He,
Shenglai Zeng,
Yingqian Cui,
Amy Liu,
Hui Liu,
Jiliang Tang
Empirical Methods in Natural Language Processing (EMNLP), 2024.
Copyright Protection in Generative AI
Jie Ren
European Conference on Artificial Intelligence (ECAI) Doctoral Consortium, 2024.
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
Jie Ren,
Yaxin Li,
Shenglai Zeng,
Han Xu,
Lingjuan Lyu,
Yue Xing,
Jiliang Tang
European Conference on Computer Vision (ECCV), 2024.
Exploring Memorization in Fine-tuned Language Models
Shenglai Zeng,
Yaxin Li,
Jie Ren,
Yiding Liu,
Han Xu,
Pengfei He,
Yue Xing,
Jiliang Tang,
Dawei Yin
Annual Meeting of the Association for Computational Linguistics (ACL), 2024.
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
Shenglai Zeng,
Jiankun Zhang,
Pengfei He,
Yue Xing,
Yiding Liu,
Han Xu,
Jie Ren,
Shuaiqiang Wang,
Dawei Yin,
Yi Chang,
Jiliang Tang
Annual Meeting of the Association for Computational Linguistics (ACL) Findings, 2024.
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
Jie Ren,
Han Xu,
Yiding Liu,
Yingqian Cui,
Shuaiqiang Wang,
Dawei Yin,
Jiliang Tang
North American Chapter of the Association for Computational Linguistics (NAACL) Findings, 2024.
Sharpness-Aware Data Poisoning Attack
Penghei He,
Han Xu,
Jie Ren,
Yingqian Cui,
Hui Liu,
Charu C. Aggarwal,
Jiliang Tang
International Conference on Learning Representations (ICLR), 2024.
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer
Yaxin Li*,
Jie Ren*,
Han Xu,
Hui Liu
Winter Conference on Applications of Computer Vision (WACV), 2024.
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Yingqian Cui*,
Jie Ren*,
Han Xu,
Pengfei He,
Hui Liu,
Lichao Sun,
Yue Xing,
Jiliang Tang
Neural Information Processing Systems Workshop on Diffusion Models, 2024.
Transferable Unlearnable Examples
Jie Ren,
Han Xu,
Yuxuan Wan,
Xingjun Ma,
Lichao Sun,
Jiliang Tang
International Conference on Learning Representations (ICLR), 2023.
Probabilistic Categorical Adversarial Attack and Adversarial Training
Penghei He,
Han Xu,
Jie Ren,
Yuxuan Wan,
Zitao Liu,
Jiliang Tang
International Conference on Machine Learning (ICML), 2023.
Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning
Tong Chen,
Hongzhi Yin,
Jie Ren,
Zi Huang,
Xiangliang Zhang,
Hao Wang
IEEE Transactions on Knowledge and Data Engineering, 2021.
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Invited Talks
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Nov. 2023: Data Protection in Deep Learning. Institute of Computing Technology, Chinese Academy of Sciences.
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Oct. 2023: Copyright Protection in Deep Generative Model. Shandong University.
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Oct. 2023: Copyright Protection in Deep Generative Model. AI Time (Tsinghua University) [website]
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Jul. 2023: DiffusionShield: A Watermark for Copyright Protection against GDMs. Qilu Youth Forum at Shandong University
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Mar. 2023: Transferable Unlearnable Examples. Fudan University
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Professional Services
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PC member: NeurIPS'24, AAAI'24-25, Web Conference'24, EMNLP'24, TKDD'23, CIKM'22-24, WSDM'23-25, ICLR'25, RecSys'23
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Reviewer: TKDD, TKDE
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Volunteer: KDD'22, TKDE
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