Publications
Selected Preprints (“*” equal contribution, “†” corresponding author, “__” advised student)
Dissecting Misalignment of Multimodal Large Language Models via Influence Function. [ArXiv] [Code]
Lijie Hu*, Chenyang Ren*, Huanyi Xie, Khouloud Saadi, Shu Yang, Jingfeng Zhang, and Di Wang.Editable Concept Bottleneck Models. [ArXiv] [Code]
Lijie Hu* , Chenyang Ren*, Zhengyu Hu*, Hongbin Lin, Cheng-Long Wang, Hui Xiong, Jingfeng Zhang, and Di Wang.Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing. [ArXiv] [Code]
Zhuoran Zhang, Yongxiang Li, Zijian Kan, Keyuan Cheng, Lijie Hu†, Di Wang.What makes your model a low-empathy or warmth person: Exploring the Origins of Personality in LLMs. [ArXiv]
Shu Yang, Shenzhe Zhu, Ruoxuan Bao, Liang Liu, Yu Cheng, Mengdi Li, Lijie Hu†, and Di Wang.Fair Text-to-Image Diffusion via Fair Mapping. [ArXiv] [Code]
Jia Li* , Lijie Hu*, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, and Di Wang.
Selected Publications (“*” equal contribution, “†” corresponding author, “__” advised student)
[NeurIPS] Towards Multi-dimensional Explanation Alignment for Medical Classification. [ArXiv] [Link] [Code]
Lijie Hu*, Songning Lai*, Wenshuo Chen*, Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, Di Wang.
The Conference on Neural Information Processing Systems (NeurIPS 2024).[ICML] Improving Interpretation Faithfulness for Vision Transformers. [Link] [ArXiv] [Code] [Video]
Lijie Hu*, Yixin Liu*, Ninghao Liu, Mengdi Huai, Lichao Sun, and Di Wang.
The 41st International Conference on Machine Learning (ICML 2024).
Selected as a Spotlight paper (3.5% acceptance rate).[ICLR] Faithful Vision-Language Interpretation via Concept Bottleneck Models. [Link] [Code] [Video]
Songning Lai*, Lijie Hu*†, Junxiao Wang, Laure Berti-Equille, and Di Wang.
The 12th International Conference on Learning Representations (ICLR 2024).[EMNLP] UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause. [Link] [ArXiv] [Code]
Guimin Hu, Zhihong Zhu, Daniel Hershcovich, Lijie Hu, Hasti Seifi, and Jiayuan Xie.
Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024 Findings).[AAAI] SEAT: Stable and Explainable Attention. [Link] [ArXiv] [Code] [Video]
Lijie Hu*, Yixin Liu*, Ninghao Liu, Mengdi Huai, Lichao Sun, and Di Wang.
The 37th AAAI Conference on Artificial Intelligence (AAAI 2023).
Selected as an Oral paper.[TKDE] Towards Stable and Explainable Attention Mechanisms.
Lijie Hu*, Xinhai Wang*, Yixin Liu*, Ninghao Liu, Mengdi Huai, Lichao Sun, and Di Wang.
Minor Revision, IEEE Transactions on Knowledge and Data Engineering (TKDE).Large Language Models / Large Multimodals (LLM/MLLM)
[COLM] Multi-hop Question Answering under Temporal Knowledge Editing. [Link] [ArXiv] [Code]
Keyuan Cheng*, Gang Lin*, Haoyang Fei*, Yuxuan Zhai, Lu Yu, Muhammad Asif Ali, Lijie Hu†, and Di Wang.
The 1st Conference on Language Modeling (COLM 2024).[COLM] MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions. [Link] [ArXiv] [Code]
Shu Yang*, Muhammad Asif Ali*, Lu Yu, Lijie Hu†, and Di Wang.
The 1st Conference on Language Modeling (COLM 2024).[EMNLP] Dissecting Fine-Tuning Unlearning in Large Language Models. [Link] [ArXiv] [Code]
Yihuai Hong, Yuelin Zou, Lijie Hu, Ziqian Zeng, Di Wang, Haiqin Yang.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024 Main).
Selected as Oral presentation.[ACM MM] SATO: Stable Text-to-Motion Framework. [Link] [ArXiv] [Code]
Wenshuo Chen, Hongru Xiao, Erhang Zhang, Lijie Hu, Lei Wang, Mengyuan Liu, and Chen Chen.
The 32nd ACM Multimedia Conference (ACM MM 2024).Privacy-preserving Artificial Intelligence
[EMNLP] Private Language Models via Truncated Laplacian Mechanism. [Link] [ArXiv] [Code]
Tianhao Huang*, Tao Yang*, Ivan Habernal, Lijie Hu, and Di Wang.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024 Main).
Selected as Oral presentation.[EACL] Differentially Private Natural Language Models: Recent Advances and Future Directions. [Link] [ArXiv] [Video]
Lijie Hu, Ivan Habernal, Lei Shen and Di Wang.
Findings of the 2024 European Chapter of the Association for Computational Linguistics (EACL 2024 Findings).[JMLR] Faster Rates of Private Stochastic Convex Optimization. [Link]
Jinyan Su, Lijie Hu, and Di Wang.
Journal of Machine Learning Research, Volume 25, 114 (2024), Pages 1−41 (JMLR).[JMLR] Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data. [Link]
Di Wang*, Lijie Hu*, Huanyu Zhang, Marco Gaboardi, and Jinhui Xu.
Journal of Machine Learning Research, Volume 24, 132 (2023), Pages 1-57 (JMLR).[ECAI] Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm. [Link]
Di Wang*, Jiahao Ding*, Lijie Hu, Zejun Xie, Miao Pan, and Jinhui Xu.
The 26th European Conference on Artificial Intelligence (ECAI 2023).[AISTATS] Privacy-preserving Sparse Generalized Eigenvalue Problem. [Link]
Lijie Hu*, Zihang Xiang*, Jiabin Liu, and Di Wang.
The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023).[TKDE] Nearly Optimal Rates of Privacy-preserving Sparse Generalized Eigenvalue Problem. [Link]
Lijie Hu*, Zihang Xiang*, Jiabin Liu, and Di Wang.
IEEE Transactions on Knowledge and Data Engineering, 2023 (01): 1-14 (TKDE).[PODS] High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data. [Link] [ArXiv] [Video]
Lijie Hu, Shuo Ni, Hanshen Xiao, and Di Wang.
Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS 2022).
Invited to The ACM Transactions on Database Systems special issue on Best of PODS 2022.
CCS Workshop on Privacy Preserving Machine Learning 2021.[ALT] Faster Rates of Differentially Private Stochastic Convex Optimization. [Link]
Jinyan Su, Lijie Hu, and Di Wang.
Proceedings of The 33rd International Conference on Algorithmic Learning Theory (ALT 2022).