Yotam Nitzan

I am a Research Scientist at Adobe in San Francisco.

Previously, I earned my Ph.D. in Computer Science from Tel Aviv University, where I was advised by Prof. Daniel Cohen-Or. I've interned at Google Research and Adobe Research (x2). Before that, I received an M.Sc. in Computer Science from Tel Aviv University and a B.Sc. in Applied Mathematics from Bar-Ilan University.

I'm focused on visual generative models, aiming to make them more interactive, intuitive, and controllable.

Email / GitHub / Google Scholar / Twitter

Selected Publications

	VLM-Guided Adaptive Negative Prompting for Creative Generation Shelly Golan, Yotam Nitzan, Zongze Wu, Or Patashnik arXiv, 2025 project page / arXiv
	Long-Context State-Space Video World Models Ryan Po, Yotam Nitzan, Richard Zhang, Berlin Chen, Tri Dao, Eli Shechtman, Gordon Wetzstein, Xun Huang ICCV, 2025 project page / arXiv
	Layer-and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers Haoran You, Connelly Barnes, Yuqian Zhou, Yan Kang, Zhenbang Du, Wei Zhou, Lingzhi Zhang, Yotam Nitzan, Xiaoyang Liu, Zhe Lin, Eli Shechtman, Sohrab Amirghodsi, Yingyan (Celine) Lin CVPR, 2025 project page / arXiv
	Lazy Diffusion Transformer for Interactive Image Editing Yotam Nitzan, Zongze Wu, Richard Zhang, Eli Shechtman, Daniel Cohen-Or, Taesung Park, Michaël Gharbi ECCV, 2024 project page / arXiv
	Domain Expansion of Image Generators Yotam Nitzan, Michaël Gharbi, Richard Zhang, Taesung Park, Jun-Yan Zhu, Daniel Cohen-Or, Eli Shechtman CVPR, 2023 project page / arXiv / code
	State-of-the-Art in the Architecture, Methods and Applications of StyleGAN Amit H Bermano, Rinon Gal, Yuval Alaluf, Ron Mokady, Yotam Nitzan, Omer Tov, Or Patashnik, Daniel Cohen-Or Eurographics, 2022 (STARs) arXiv
	MyStyle: A Personalized Generative Prior Yotam Nitzan, Kfir Aberman, Qiurui He, Orly Liba, Michal Yarom, Yossi Gandelsman, Inbar Mosseri, Yael Pritch, Daniel Cohen-Or SIGGRAPH Asia, 2022 (Journal Track) project page / arXiv / video / code
	StyleAlign: Analysis and Applications of Aligned StyleGAN Models Zongze Wu, Yotam Nitzan, Eli Shechtman, Dani Lischinski ICLR, 2022 (Oral) arXiv / video / code
	LARGE: Latent-Based Regression through GAN Semantics Yotam Nitzan, Rinon Gal, Ofir Brenner, Daniel Cohen-Or CVPR, 2022 arXiv / code
	Designing an Encoder for StyleGAN Image Manipulation Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, Daniel Cohen-Or SIGGRAPH, 2021 arXiv / code
	Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, Daniel Cohen-Or CVPR, 2021 project page / arXiv / code
	Face Identity Disentanglement via Latent Space Mapping Yotam Nitzan, Amit Bermano, Yangyan Li, Daniel Cohen-Or SIGGRAPH Asia, 2020 project page / arXiv / code

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