Hi there 👋👋 !

I’m Boheng Li (李勃衡), a Ph.D. student at the College of Computing and Data Science (CCDS), Nanyang Technological University, Singapore, under the supervision of Prof. Tianwei Zhang. I received my B.E. from the School of Cyber Science and Engineering (SCSE), Wuhan University (WHU), China, where I was advised by Prof. Run Wang.

My research interests focus on trustworthy machine learning, with a particular emphasis on responsible (multimodal) generative models.

🌟🌟 I am open to discussions and potential collaboration opportunities. If you’re interested in working with me, feel free to contact me via Email or WeChat.

🔥 News

📝 Selected Publications

$^\dagger$: equal contribution

• Towards Resilient Safety-driven Unlearning for Diffusion Models against Downstream Fine-tuning
  Boheng Li, Renjie Gu, Junjie Wang, Leyi Qi, Yiming Li, Run Wang, Zhan Qin, Tianwei Zhang
  arXiv, 2025

• DREAM: Scalable Red Teaming for Text-to-Image Generative Systems via Distribution Modeling
  Boheng Li, Junjie Wang, Yiming Li, Zhiyang Hu, Leyi Qi, Jianshuo Dong, Run Wang, Han Qiu, Zhan Qin, Tianwei Zhang
  The IEEE Symposium on Security and Privacy (S&P), 2026 (To Appear)

• Towards Reliable Verification of Unauthorized Data Usage in Personalized Text-to-Image Diffusion Models
  Boheng Li, Yanhao Wei, Yankai Fu, Zhenting Wang, Yiming Li, Jie Zhang, Run Wang, Tianwei Zhang
  The IEEE Symposium on Security and Privacy (S&P), 2025

• Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation
  Boheng Li$^\dagger$, Yishuo Cai$^\dagger$, Jisong Cai, Yiming Li, Han Qiu, Run Wang, Tianwei Zhang
  The International Conference on Machine Learning (ICML), 2024

• Nearest Is Not Dearest: Towards Practical Defense against Quantization-conditioned Backdoor Attacks
  Boheng Li, Yishuo Cai, Haowei Li, Feng Xue, Zhifeng Li, Yiming Li
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

• Is Difficulty Calibration All We Need? Towards More Practical Membership Inference Attacks
  Yu He$^\dagger$, Boheng Li$^\dagger$, Yao Wang, Mengda Yang, Juan Wang, Hongxin Hu, and Xingyu Zhao
  The ACM Conference on Computer and Communications Security (CCS), 2024

• What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Networks
  Ziheng Huang$^\dagger$, Boheng Li$^\dagger$, Yan Cai, Run Wang, Shangwei Guo, Liming Fang, Jing Chen, Lina Wang
  The International Conference on Computer Vision (ICCV), 2023

🎡 Activities

Academic Services

• Program Committee, The IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2026.
• Artifact Evaluation Committee, The Network and Distributed System Security Symposium (NDSS), 2026.
• Artifact Evaluation Committee, The USENIX Security Symposium (USENIX Security), 2025.
• Reviewer, The International Conference on Machine Learning (ICML), 2025. (ICML’25 Top Reviewer Award)
• Reviewer, The International Conference on Learning Representations (ICLR), 2025, 2026. (ICLR’25 Notable Reviewer Award)
• Reviewer, Annual Conference on Neural Information Processing Systems (NeurIPS), 2024, 2025.
• Reviewer, The International Conference on Computer Vision (ICCV), 2025.
• Reviewer, ACM Multimedia Conference (MM), 2024, 2025. (MM’24 Outstanding Reviewer)
• Reviewer, The International Conference on Artificial Intelligence and Statistics (AISTATS), 2025, 2026.
• Reviewer, The Transactions on Machine Learning Research (TMLR), 2025.
• Reviewer, The IEEE Transactions on Dependable and Secure Computing (TDSC), 2025.
• Reviewer, The IEEE Transactions on Information Forensics & Security (TIFS), 2025.
• Reviewer, The Transactions on Image Processing (TIP), 2025.
• Reviewer, The IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2025.
• Reviewer, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2023.