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Jie Ren 任杰
I am a fourth-year Ph.D. student in 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 received my bachelor degree from Tsinghua University.
My research interests lie in Trustworthy and Interpretable AI, with a focus on data and model protection in GenAI.
Email: renjie3 [at] msu.edu
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News
[Feb 2025] One paper accepted by CVPR 2025!
[Jan 2025] One paper accepted by AISTATS 2025!
[Jan 2025] One paper accepted by WWW 2025 [Oral]!
[Nov 2024] One paper accepted by TMLR!
[Sep 2024] One paper accepted by EMNLP 2024!
[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 2024!
[May 2024] Two papers accepted by ACL 2024!
[Mar 2024] I will start my internship at Sony AI in March.
[Mar 2024] One paper is accepted by NAACL 2024 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)
A General Framework to Enhance Fine-tuning-based LLM Unlearning
Jie Ren,
Zhenwei Dai,
Xianfeng Tang,
Hui Liu,
Jingying Zeng,
Zhen Li,
Rahul Goutam,
Suhang Wang,
Yue Xing,
Qi He,
Hui Liu
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
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
[Survey] 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
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)
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models
CVPR 2025
Jie Ren*,
Kangrui Chen*,
Yingqian Cui,
Shenglai Zeng,
Hui Liu,
Yue Xing,
Jiliang Tang,
Lingjuan Lyu
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models
WWW 2025 [Oral]
Jie Ren,
Kangrui Chen,
Chen Chen,
Vikash Sehwag,
Yue Xing,
Jiliang Tang,
Lingjuan Lyu
Superiority of Multi-Head Attention in In-Context Linear Regression
AISTATS 2025
Yingqian Cui,
Jie Ren,
Pengfei He,
Jiliang Tang,
Yue Xing
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
SIGKDD Explorations 2024
Yingqian Cui*,
Jie Ren*,
Han Xu,
Pengfei He,
Hui Liu,
Lichao Sun,
Yue Xing,
Jiliang Tang
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
SIGKDD Explorations 2024
Yingqian Cui,
Jie Ren,
Yuping Lin,
Han Xu,
Pengfei He,
Yue Xing,
Wenqi Fan,
Hui Liu,
Jiliang Tang
Stealthy Backdoor Attack via Confidence-driven Sampling
TMLR 2024
Pengfei He,
Han Xu,
Jie Ren,
Yingqian Cui,
Shenglai Zeng,
Yue Xing,
Jiliang Tang,
Makoto Yamada,
Mohammad Sabokrou
On the Generalization of Training-based ChatGPT Detection Methods
EMNLP 2024 Findings
Han Xu,
Jie Ren,
Pengfei He,
Shenglai Zeng,
Yingqian Cui,
Amy Liu,
Hui Liu,
Jiliang Tang
Copyright Protection in Generative AI
ECAI 2024 Doctoral Consortium
Jie Ren
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
ECCV 2024
Jie Ren,
Yaxin Li,
Shenglai Zeng,
Han Xu,
Lingjuan Lyu,
Yue Xing,
Jiliang Tang
Exploring Memorization in Fine-tuned Language Models
ACL 2024
Shenglai Zeng,
Yaxin Li,
Jie Ren,
Yiding Liu,
Han Xu,
Pengfei He,
Yue Xing,
Jiliang Tang,
Dawei Yin
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
ACL 2024 Findings
Shenglai Zeng,
Jiankun Zhang,
Pengfei He,
Yue Xing,
Yiding Liu,
Han Xu,
Jie Ren,
Shuaiqiang Wang,
Dawei Yin,
Yi Chang,
Jiliang Tang
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
NAACL 2024 Findings
Jie Ren,
Han Xu,
Yiding Liu,
Yingqian Cui,
Shuaiqiang Wang,
Dawei Yin,
Jiliang Tang
Sharpness-Aware Data Poisoning Attack
ICLR 2024 [Spotlight, top %5]
Penghei He,
Han Xu,
Jie Ren,
Yingqian Cui,
Hui Liu,
Charu C. Aggarwal,
Jiliang Tang
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer
WACV 2024
Yaxin Li*,
Jie Ren*,
Han Xu,
Hui Liu
Transferable Unlearnable Examples
ICLR 2023
Jie Ren,
Han Xu,
Yuxuan Wan,
Xingjun Ma,
Lichao Sun,
Jiliang Tang
Probabilistic Categorical Adversarial Attack and Adversarial Training
ICML 2023
Penghei He,
Han Xu,
Jie Ren,
Yuxuan Wan,
Zitao Liu,
Jiliang Tang
Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning
TKDE 2021
Tong Chen,
Hongzhi Yin,
Jie Ren,
Zi Huang,
Xiangliang Zhang,
Hao Wang
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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'24-25, AAAI'24-25, WebConf'24-25, EMNLP'24, CIKM'22-24, WSDM'23-25, ICLR'25, RecSys'23, CVPR'25, NAACL'25, ICML'25, ICCV'25
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Reviewer: TKDD, TKDE
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Volunteer: KDD'22
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