Jie Ren

Trustworthy AIInterpretable AIReliable Reasoning & Agents

I am a Postdoctoral Associate at MIT CSAIL, working with Neil Thompson and Jonathan Rosenfeld. I received my Ph.D. in Computer Science from Michigan State University, advised by Jiliang Tang, and my B.E. from Tsinghua University.

My research aims to advance trustworthy AI through a deeper understanding of the behaviors, underlying mechanisms, and limitations of AI, extending from individual models to reasoning and agentic systems.

I was selected as an ML and Systems Rising Star (MLCommons) and a Rising Star in AI (KAUST), and I serve as an Area Chair for ICLR, ICML, and ARR.

rjie [at] mit.edu Google Scholar GitHub LinkedIn

News

Oct 2026 Invited to serve as an Area Chair for ARR Oct. 2026.
Oct 2026 Invited to serve as an Area Chair for ICML 2027.
Sep 2026 Invited to serve as an Area Chair for ICLR 2027.
Sep 2026 One paper accepted by NeurIPS 2026.
May 2026 Glad to be recognized as a Gold Reviewer by ICML 2026.
May 2026 One paper accepted by KDD 2026.
Apr 2026 Selected as ML and Systems Rising Star, MLCommons.
Jan 2026 I joined MIT CSAIL as a Postdoctoral Associate.
Dec 2025 Selected as Rising Star in AI, KAUST, Saudi Arabia.
Nov 2025 Received the NeurIPS Scholar Award.
Nov 2025 One paper selected as oral presentation by NeurIPS Workshop on GenProCC.
Sep 2025 One paper accepted by NeurIPS 2025!
Aug 2025 Two papers accepted by EMNLP 2025!
May 2025 I will start my internship at ByteDance in Summer 2025!
May 2025 One paper accepted by ACL 2025!
Feb 2025 One paper accepted by CVPR 2025!
Jan 2025 One paper accepted by WWW 2025 (Oral)!
Jan 2025 One paper accepted by AISTATS 2025!
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 One paper accepted by NAACL 2024 Findings.
Mar 2024 I will start my internship at Sony AI in March.
Feb 2024 The preprint of our survey, Copyright Protection in Generative AI: A Technical Perspective, is released.

Research

Understanding why AI systems behave as they do is the thread that runs through my work: it guides my primary focus on data protection, and, together with lessons from that work, drives my recent expansion to reasoning and agentic systems.

My Trustworthy AI Focus

Data Protection in AI

Helping data owners protect their data, and model developers use data responsibly.

Research Philosophy

Understanding & Controlling AI Behaviors

Uncovering the mechanisms behind AI to guide targeted interventions.

Recent Expansion

Reliable Reasoning & Agentic Systems

Making LLM reasoning and agentic systems more reliable and efficient.

Preprints

Goal-Aware Dynamic Multi-Agent Collaboration for Long-Horizon Tasks

Xu Shen, Lingyong Yan, Shuaiqiang Wang, Zhikai Chen, Jiliang Tang, Jie Ren

TriAct: Learning When to Stop, Continue, and Sample for Adaptive Test-Time Scaling in Latent Reasoning

Jie Ren*, Jinhua Si*, Yingqian Cui, Shuaiqiang Wang, Lingyong Yan, Dawei Yin, Kai Guo, Yue Xing, Hui Liu

Beyond Ranking: Making Long-term Multi-modal Memory Addressable

Kai Guo, Xinnan Dai, Shenglai Zeng, Zhikai Chen, Xianxuan Long, Jiayuan Ding, Jie Ren, Haoyu Han, Hui Liu

Paper

Machine Unlearning for Large Language Models (Survey)

Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu

Paper

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

Paper

Publications

Early Signals, Strong Decisions: Prefix-Guided Sampling for Parallel Test-Time Scaling

Jie Ren, Jonathan Rosenfeld, Neil Thompson

NeurIPS 2026Paper Code

Why Retrieval-Augmented Generation Fails: A Graph Perspective

Kai Guo, Xinnan Dai, Zhibo Zhang, Nuohan Lin, Shenglai Zeng, Jie Ren, Haoyu Han, Jiliang Tang

KDD 2026Paper Code

Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy

Jie Ren, Zhenwei Dai, Xianfeng Tang, Yue Xing, Shenglai Zeng, Hui Liu, Jingying Zeng, Qiankun Peng, Samarth Varshney, Suhang Wang, Qi He, Charu C. Aggarwal, Hui Liu

NeurIPS 2025Paper Code

Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation

Jiankun Zhang, Shenglai Zeng, Jie Ren, Tianqi Zheng, Hui Liu, Xianfeng Tang, Hui Liu, Yi Chang

EMNLP 2025Paper Code

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

EMNLP 2025Paper Code

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

ACL 2025 FindingsPaper Code

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

CVPR 2025Paper Code

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

WWW 2025OralPaper Code

Superiority of Multi-Head Attention in In-Context Linear Regression

Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing

AISTATS 2025Paper

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

SIGKDD Explorations 2024Paper Code

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, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang

SIGKDD Explorations 2024Paper Code

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

TMLR 2024Paper Code

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

EMNLP 2024 FindingsPaper Dataset

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

ECCV 2024Paper Code

Exploring Memorization in Fine-tuned Language Models

Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin

ACL 2024Paper

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

ACL 2024 FindingsPaper Code

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

NAACL 2024 FindingsPaper Code

Sharpness-Aware Data Poisoning Attack

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang

ICLR 2024Spotlight, top 5%Paper Code

Neural Style Protection: Counteracting Unauthorized Neural Style Transfer

Yaxin Li*, Jie Ren*, Han Xu, Hui Liu

WACV 2024Paper

Transferable Unlearnable Examples

Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang

ICLR 2023Paper Code

Probabilistic Categorical Adversarial Attack and Adversarial Training

Pengfei He, Han Xu, Jie Ren, Yuxuan Wan, Zitao Liu, Jiliang Tang

ICML 2023Paper

Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning

Tong Chen, Hongzhi Yin, Jie Ren, Zi Huang, Xiangliang Zhang, Hao Wang

TKDE 2021Paper

Workshops

EnTruth: Tracing the Unauthorized Dataset Usage in Diffusion Models

Jie Ren, Yingqian Cui, Chen Chen, Yue Xing, Hui Liu, Lingjuan Lyu

NeurIPS 2025 Workshop on GenProCCOralPaper

No papers match the selected areas.

Awards & Honors

2026ML and Systems Rising Star, MLCommons (39 selected worldwide)
2026Rising Star in AI, KAUST (25 selected worldwide; declined due to travel constraints)
2026ICML Gold Reviewer Award
2025NeurIPS Scholar Award
2025Graduate Experiential Education Fellowship, Michigan State University
2019Zijing Outstanding Instructor, Tsinghua University
2016Social Service Outstanding Scholarship, Tsinghua University

Teaching

Fall 2023Teaching Assistant, CSE 881 Data Mining (graduate), Michigan State University
Spring 2023Teaching Assistant, CSE 482 Big Data Analysis, Michigan State University
2019Instructor, International Undergraduate Freshmen Foundation Program, Tsinghua University
2016–2019Instructor, Summer School, Tsinghua University (2016, 2017, 2019)
Fall 2016Teaching Assistant, Introduction to the Social Service of College Students, Tsinghua University

Service

Area Chair: ICLR 2027, ICML 2027, ARR 2027, NeurIPS GenAI4Health Workshop 2026
PC Member: NeurIPS, ICLR, ICML, AAAI, ACL, EMNLP, NAACL, CVPR, ICCV, ECCV, WACV, WSDM, CIKM, WWW, RecSys
Journals: TKDD, TKDE, TIST, TIP, TIFS, TMLR, ACM Computing Surveys
Volunteer: WWW 2025, KDD 2022; Organizer, Girls Math and Science Day at MSU 2023