Zhao, Yulai

13 publications

ICLR 2026 Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design Xingyu Su, Xiner Li, Masatoshi Uehara, Sunwoo Kim, Yulai Zhao, Gabriele Scalia, Ehsan Hajiramezanali, Tommaso Biancalani, Degui Zhi, Shuiwang Ji

ICLR 2025 Adding Conditional Control to Diffusion Models with Reinforcement Learning Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sunyuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali

NeurIPS 2025 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICML 2025 Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani

NeurIPS 2024 Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gokcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani

NeurIPSW 2024 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICML 2024 Feedback Efficient Online Fine-Tuning of Diffusion Models Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M Tseng, Sergey Levine, Tommaso Biancalani

ICLR 2024 Provably Efficient CVaR RL in Low-Rank MDPs Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee

AISTATS 2023 Blessing of Class Diversity in Pre-Training Yulai Zhao, Jianshu Chen, Simon Du

ICML 2023 Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee

NeurIPSW 2023 Provably Efficient CVaR RL in Low-Rank MDPs Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason Lee

AISTATS 2022 Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games Yulai Zhao, Yuandong Tian, Jason Lee, Simon Du

NeurIPSW 2022 Optimizing the Performative Risk Under Weak Convexity Assumptions Yulai Zhao