✨ About me

Bonjour, I am a first-year Ph.D. student in the Department of Computer Sciences at the University of Wisconsin–Madison, advised by Prof. Sharon Yixuan 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 interests lie broadly in Trustworthy AI, with a particular focus on:

• (a) Foundation Model (e.g. LLM/LMM) Alignment
• (b) Foundation Model (e.g. LLM/LMM) Attack/Defence.
• (c) Semi-supervised Learning (e.g. classification and segmentation)
• (d) Responsible AIGC (e.g. talking head generation, t2i/t2v generation model)

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

📰 News

• 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.

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]

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.

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, ICLR’24, ICML’24-25, ACM MM’24, ECCV’24, NeurIPS’24-25, AAAI’26

🙌 Open Source Contribution

• Github: Open Sora Plan, Peking University, Yuan Group, Contributors, 10.9k Stars.
  • Role: Contribute the evaluation code for video generation, e.g. Clip-Score, FVD, SSIM, LPIPS, and PSNR.

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