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Sheng-Yu Wang PhD Student Carnegie Mellon University shengyu2 at andrew.cmu.edu [GitHub] [Google Scholar] [CV] I am a final year PhD at CMU, advised by Jun-Yan Zhu. These days, I am also working closely with Richard Zhang, Alexei (Alyosha) Efros, Aaron Hertzmann, and David Bau. I am generally interested in image synthesis and understanding deep neural networks. During undergrad, I worked at BAIR with Oliver Wang, Richard Zhang, Andrew Owens and Alexei (Alyosha) Efros. In the past, I have worked on image forensics, and condensed matter physics. My research is supported by Google PhD Fellowship, Snap Research Fellowship, and Uber Presidential Fellowship. I am on the job market in Spring 2026. Publications NP-Edit: Learning an Image Editing Model without Image Editing Pairs Nupur Kumari, Sheng-Yu Wang, Nanxuan Zhao, Yotam Nitzan, Yuheng Li, Krishna Kumar Singh, Richard Zhang, Eli Shechtman, Jun-Yan Zhu, Xun Huang. Tech Report, 2025. [Paper] [Webpage] [Bibtex] Fast Data Attribution for Text-to-Image Models Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Richard Zhang, Jun-Yan Zhu. In NeurIPS, 2025. [Paper] [Webpage] [GitHub] [Bibtex] Identifying Prompted Artist Names from Generated Images Grase Su, Sheng-Yu Wang, Aaron Hertzmann, Eli Shechtman, Jun-Yan Zhu, Richard Zhang. Tech Report, 2025. [Paper] [Webpage] [Dataset] [GitHub] [Bibtex] Data Attribution for Text-to-Image Models by Unlearning Synthesized Images Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang. In NeurIPS, 2024. [Paper] [Webpage] [GitHub] [Bibtex] Customizing Text-to-Image Models with a Single Image Pair Maxwell Jones, Sheng-Yu Wang, Nupur Kumari, David Bau, Jun-Yan Zhu. In SIGGRAPH Asia, 2024. [Paper] [Webpage] [GitHub] [Bibtex] Evaluating Data Attribution for Text-to-Image Models Sheng-Yu Wang, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang. In ICCV, 2023. [Paper] [Webpage] [GitHub] [Bibtex] Ablating Concepts in Text-to-Image Diffusion Models Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu. In ICCV, 2023. [Paper] [Webpage] [GitHub] [Bibtex] Content-Based Search for Deep Generative Models Daohan Lu*, Sheng-Yu Wang*, Nupur Kumari*, Rohan Agarwal*, Mia Tang, David Bau, Jun-Yan Zhu. In SIGGRAPH Asia, 2023. [Modelverse] [Webpage] [Github] [Paper] [Video] [BibTex] Rewriting Geometric Rules of a GAN Sheng-Yu Wang, David Bau, Jun-Yan Zhu. In SIGGRAPH, 2022. [Paper] [Webpage] [GitHub] [Bibtex] Sketch Your Own GAN Sheng-Yu Wang, David Bau, Jun-Yan Zhu. In ICCV, 2021. [Paper] [Webpage] [GitHub] [Bibtex] CNN-generated images are surprisingly easy to spot...for now Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, Alexei A. Efros. In CVPR, 2020 (oral presentation). [Paper] [Webpage] [GitHub] [Bibtex] Detecting Photoshopped Faces by Scripting Photoshop Sheng-Yu Wang, Oliver Wang, Andrew Owens, Richard Zhang, Alexei A. Efros. In ICCV, 2019. [Paper] [Webpage] [GitHub] [Poster] [Adobe Max] [Bibtex] Reversible writing of high mobility and high carrier density doping patterns in two-dimensional van der Waals heterostructures Wu Shi, Salman Khan, Lili Jiang, Sheng-Yu Wang, Hsin-Zon Tsai, Dillon Wong, Takashi Taniguchi, Kenji Watanabe, Fen Wang, Michael Crommie, Alex Zettl. Nature Electronics. [Paper] Many thanks to Richard Zhang for sharing his website template!