Zizhao Zhang

I completed my PhD since 2019. I also spent great time at Siemens Research and Facebook AI Research (FAIR). My PhD research focus was computer vision and deep learning, especially their applications in medical imaging and healthcare.

At present, I do research and development for Gemini at Google.  

Selected Publications

[ArXiv' 25] Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities, Gemini Team, Google

[ACL'25] SkillVerse - Assessing and Enhancing LLMs with Tree Evaluation, Yufei Tian, Jiao Sun, Nanyun Peng, Zizhao Zhang. ACL 2025.

[ArXiv'24] Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context, Gemini Team, Google

[NAACL'24] CodecLM: Aligning Language Models with Tailored Synthetic Data, Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister

[ArXiv'23] Gemini: a family of highly capable multimodal models, Gemini Team, Google

[ACL'23] QueryForm: A Simple Zero-shot Form Entity Query Framework, Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer Dy, Vincent Perot, Tomas Pfister

[ECCV'22] DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning, Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, Tomas Pfister (code)

[ECCV'22] Learning Instance-Specific Adaptation for Cross-Domain Segmentation, Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang (project page) (code)

[CVPR'22] Learning to Prompt for Continual Learning, Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, Tomas Pfister (code)

[AAAI'22] Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding, Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Sercan O Arik, Tomas Pfister (code and models) (pytorch code in timm), Oral Presentation

[AAAI'22] Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts, Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister

[NeurIPS'21] Improved Transformer for High-Resolution GANs, Long Zhao, Zizhao Zhang, Ting Chen, Dimitris N. Metaxas, Han Zhang (code)

[ICCV'21] Learning Fast Sample Re-weighting Without Reward Data, Zizhao Zhang, Tomas Pfister (code)

[ICLR'21] PseudoSeg: Designing Pseudo Labels for Semantic Segmentation, Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister (code)

[AAAI'21] Improved Consistency Regularization for GANs, Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang

[NeurIPS'20] FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence, Kihyuk Sohn*, David Berthelot*, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel (code)

[ECCV'20] Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost, Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan O Arik, Larry S Davis, Tomas Pfister

[CVPR'20] Distilling Effective Supervision from Severe Label Noise, Zizhao Zhang, Han Zhang, Sercan O Arik, Honglak Lee, Tomas Pfister (code)

[ICLR'20] Consistency Regularization for Generative Adversarial Networks, Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee

[ICLR'20] Distance-Based Learning from Errors for Confidence Calibration, Chen Xing, Sercan Arik, Zizhao Zhang, Tomas Pfister (code)

Before 2020