✨ About me

Bonjour, I am a Ph.D. student in the Department of Computer Sciences at the University of Wisconsin–Madison, advised by Prof. Sharon Li. Before this, I obtain the graduate degree of computer application technology at Peking University, advised by Prof. Jie Chen. I received a B.S. degree from the College of Computer Science (Elite Class), in Jilin University, in 2022.

My research focuses on the intersection of Trustworthy Multimodal Systems, with a particular focus on:

• Interpretability and Mechanistic Alignment: Investigating the internal decision-making of multimodal models to ensure their reasoning is transparent and safety-aligned.
• Alignment Tuning and Post-training: Optimizing post-training paradigms (e.g., SFT, DPO) to enhance cross-modal capability and mitigate hallucinations in large multimodal models.

😃 I am seeking research collaboration opportunities. Feel free to contact me if you are interested in potential collaboration!

📰 News

• 2026/04: 🎉 One paper about Multimodal Interpretability is accepted by ACL 2026 as main paper.
• 2024/12: 🎉 One paper (AnyTalk about Talking Head Generation is accepted by AAAI 2025.
• 2024/09: 🎉 One paper (SubgDiff about molecular 3D conformation generation is accepted by NeurIPS 2024.
• 2024/07: 🎉 Two papers (Adashield about VLM Safety and ParCo about Text-to-Motion Synthesis) are accepted by ECCV 2024.
• 2024/04: 🚀 We release an open-source repository about Awesome-T2I-safety-Papers.
• 2023/10: 🎉 One paper (TIDA) about open-set semi-supervised learning is accepted by NeurIPS 2023.
• 2023/03: 🎉 Two papers (OSP about robust semi-supervised learning and FPR about semi-supervised semantic segmentation) are accepted by CVPR 2023.

💻 Selected Publication

My full paper list is shown at Google Scholar.

Multimodal Interpretability

• ACL 2026 Why Multimodal In-Context Learning Lags Behind? Unveiling the Inner Mechanisms and Bottlenecks, Yu Wang, Sharon Li. [Code]

Safety AI

• ECCV 2024 AdaShield: Safeguarding Multimodal LLMs from Structure-based Attack via Adaptive Shield Prompting, Yu Wang, Xiaogeng Liu , Yu Li, Muhao Chen, Chaowei Xiao. [Code]
• Awesome Github Repo Awesome-T2I-safety-Papers.

Open-set/Robust Semi-supervised Learning

• NeurIPS 2023 Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning, Yu Wang,Zhun Zhong, Pengchong Qiao, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen. [Code]
• CVPR 2023 Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning, Yu Wang*, Pengchong Qiao*, Chang Liu, Guoli Song, Xiawu Zheng, Jie Chen. [Code]

AIGC

• AAAI 2025 AnyTalk: Multi-modal Driven Multi-domain Talking Head Generation, Yu Wang, Yunfei Liu, Fa-Ting Hong, Meng Cao, Lijian Lin, Yu Li

🎖 Honors and Awards

• 2025/05: Outstanding Graduate, Peking University (University Graduation Honor) (Top 5%)
• 2024/11: Tiehan Scholarship, Peking University (Top 5%)
• 2024/11: Merit Student, Peking University (Top 10%)
• 2023/11: Merit Student, Peking University (Top 10%)
• 2023/03: Excellent Papers of China Computer Federation Computer Application Conference, CCF Conference on Computer Applications (Top 1%)
• 2022/12: Jilin Bank Wang Xianghao Scholarship, Jilin University (Top 1%)
• 2021/11: National Scholarship, Jilin University (Top 1%)
• 2020/10: National Inspirational Scholarship, Jilin University (Top 1%)

💪 Academic Service

• PC Member: CVPR’24-26, ICLR’24-26, ICML’24-26, ACM MM’24, ECCV’24,26, NeurIPS’24-25, AAAI’26

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