🎓 About Me

I am Zeyu Qin (秦泽钰), a Ph.D. student of Computer Science & Engineering at Hong Kong University of Science and Technology (HKUST). My advisors are Prof. Minhao Cheng and Prof. Nevin L. Zhang. My research interest is broadly on AI Safety, Interpretability, and Alignment. Currently, my focus is on enhancing the safety and interpretability of Large Pretrained Models, specifically for Eliciting Latent Knowledge (ELK).

I am very fortunate to have worked with lots of distinguished researchers: Prof. Baoyuan Wu, Dr. Yanbo Fan, Dr. Li Shen, Prof. Hongyuan Zha, Dr. Jiancong Xiao, and Prof. Piji Li. I had an amazing four years at LGU with my good friends from Room 310 and Room 224. Miss you, guys!

📜 News

• 2023.10: I will go to New Orleans to attend NeurIPS 2023.
• 2023.09: Two papers (one spotlight) have been accepted by NeurIPS 2023: 1. Feature shift tuning which achieves SOTA purification performance against backdoor attacks; 2. Spotlight! Imitation learning from imperfect demonstrations (See Ziniu Li).
• 2023.05: New work has been accepted by KDD 2023: The first study about robustness from personalization in FL against backdoor attacks.
• 2022.10: I will go to New Orleans to attend NeurIPS 2022.
• 2022.09: The paper about adversarial transferability (Reverse Adversarial Perturbation) was accepted by NeurIPS 2022.
• 2021.09: The paper about defense against query-based attacks (Random Noise Defense) was accepted by NeurIPS 2021.

📝 Publications

* denoting equal contribution

• Towards Stable Backdoor Purification through Feature Shift Tuning
  Rui Min*, Zeyu Qin*, Li Shen, Minhao Cheng.
  In Advances in Neural Information Processing Systems (NeurIPS), 2023. [arxiv] [OpenReview] [code]

• Imitation Learning from Imperfection: Theoretical Justifications and Algorithms (Spotlight!)
  Ziniu Li*, Tian Xu*, Zeyu Qin, Yang Yu, Zhiquan Luo.
  In Advances in Neural Information Processing Systems (NeurIPS), 2023. [OpenReview]
  (This is excellent work from Ziniu and Tian. I only conducted part of the experiments. I almost have no idea about Imitation Learning 😂.)

• Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
  Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Boling Ding, Minhao Cheng.
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. [arxiv] [code]

• Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators
  Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong.
  The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. [arxiv]

• Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis.
  Jiancong Xiao, Zeyu Qin, Yanbo Fan, Baoyuan Wu, Jue Wang, Zhi-Quan Luo.
  ICML 2023 Workshop AdvML-Frontiers, 2023 [arxiv]

• Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation
  Zeyu Qin*, Yanbo Fan*, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu.
  In Advances in Neural Information Processing Systems (NeurIPS), 2022. [arxiv] [OpenReview] [code]

• Random Noise Defense Against Query-Based Black-Box Attacks
  Zeyu Qin, Yanbo Fan, Hongyuan Zha, Baoyuan Wu.
  In Advances in Neural Information Processing Systems (NeurIPS), 2021. [arxiv] [OpenReview] [code]

📝 Preprints

* denoting equal contribution

• Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping
  Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao.
  Arxiv, 2024. [arxiv]

🎖 Honors and Awards

• 2022.10, NeurIPS 2022 Scholar Award
• 2021.04, Poster Runner-Up Reward of The First Doctoral and Postdoctoral Academic Forum of Shenzhen Research Institute of Big Data

📖 Educations

• 2022.08 - Now, Ph.D. student in Computer Science & Engineering, The Hong Kong University of Science and Technology.
• 2018.08 - 2022.05 (Ph.D. –> M.Phil), M.Phil in Computer and Information Engineering, The Chinese University of Hong Kong, Shenzhen.
• 2014.09 - 2018.06, B.Eng. in Information Engineering, Nanjing University of Aeronautics and Astronautics.

💬 Invited Talks

• 2022.10, Adversarial Transferability in AI Times Forum.

💻 Internships

• Summer 2022: Research Intern, Alibaba Damo Academy, Hangzhou, China
• July 2021 – May 2022: Research Intern, Tencent AI Lab, Shenzhen, China
• January 2020 – October 2020: Research Intern, Tencent AI Lab, Shenzhen, China