PhD Student (Third Year), Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA. Email: cuiyingq@msu.edu Office: 428 S Shaw Lane, Engineering Building 3308, East Lansing, MI Co-advised by Prof. Jiliang Tang and Prof. Yue Xing Currently working as an Applied Scientist Intern at Amazon.com Inc., USA (Starting October 2025) [CV] [GitHub] [LinkedIn] [Google Scholar]

Research Interests

• Adversarial Attacks and Defenses
• Trustworthy AI
• Theory in Deep Learning

Conference and Journal Papers

• DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models
  Yingqian Cui*, Jie Ren*, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang
  ACM SIG Conference on Knowledge Discovery and Data Mining (SIGKDD) Explorations, 2024
• 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
  ACM SIG Conference on Knowledge Discovery and Data Mining (SIGKDD) Explorations, 2024
• A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
  Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing
  Artificial Intelligence and Statistics (AISTAT), 2025
• Superiority of Multi-Head Attention in In-Context Linear Regression
  Yingqian Cui, Jie Ren, Pengfei He, Hui Liu, Jiliang Tang, Yue Xing
  Artificial Intelligence and Statistics (AISTAT), 2025
• 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
  Conference on Computer Vision and Pattern Recognition (CVPR), 2025
• Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study
  Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing
  Stat, 2024
• Sharpness-Aware Data Poisoning Attack
  Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang
  Spotlight paper (5%) at International Conference on Learning Representations (ICLR), 2024
• 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
• A Robust Semantics-Based Watermark for Large Language Models Against Paraphrasing
  Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 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
  Findings of the Association for Computational Linguistics: EMNLP 2024

Preprints

• Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
  Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
• Copyright Protection in Generative AI: A Technical Perspective
  Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang
• 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

Teaching

• CSE 482 Big Data Analysis: Fall 2023, Michigan State University.
  Teaching Assistant.
• CSE 480 Database Systems: Spring 2024, Michigan State University.
  Teaching Assistant.