Wang, Chaoqi

19 publications

ICLRW 2025 GRAPE: Generalizing Robot Policy via Preference Alignment Zijian Zhang, Kaiyuan Zheng, Zhaorun Chen, Joel Jang, Yi Li, Siwei Han, Chaoqi Wang, Mingyu Ding, Dieter Fox, Huaxiu Yao

NeurIPS 2025 MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? Zhaorun Chen, Zichen Wen, Yichao Du, Yiyang Zhou, Chenhang Cui, Siwei Han, Zhenzhen Weng, Chaoqi Wang, Zhengwei Tong, Leria Huang, Canyu Chen, Haoqin Tu, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao

ICLR 2024 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

AISTATS 2024 Don’t Be Pessimistic Too Early: Look K Steps Ahead! Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen

ICMLW 2024 MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge? Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Leria Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao

AISTATS 2024 Model-Based Policy Optimization Under Approximate Bayesian Inference Chaoqi Wang, Yuxin Chen, Kevin Murphy

ICML 2023 Active Policy Improvement from Multiple Black-Box Oracles Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew Walter, Yuxin Chen

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

NeurIPSW 2023 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

NeurIPS 2023 Follow-Ups Also Matter: Improving Contextual Bandits via Post-Serving Contexts Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu

ICMLW 2023 Follow-Ups Also Matter: Improving Contextual Bandits via Post-Serving Contexts Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru, Haifeng Xu

ICMLW 2023 Iterative Machine Teaching for Black-Box Markov Learners Chaoqi Wang, Sandra Zilles, Adish Singla, Yuxin Chen

ICMLW 2023 Model-Based Policy Optimization Under Approximate Bayesian Inference Chaoqi Wang, Yuxin Chen, Kevin Patrick Murphy

AISTATS 2021 Beyond Marginal Uncertainty: How Accurately Can Bayesian Regression Models Estimate Posterior Predictive Correlations? Chaoqi Wang, Shengyang Sun, Roger Grosse

NeurIPS 2021 Teaching an Active Learner with Contrastive Examples Chaoqi Wang, Adish Singla, Yuxin Chen

ICLR 2020 Picking Winning Tickets Before Training by Preserving Gradient Flow Chaoqi Wang, Guodong Zhang, Roger Grosse

ICML 2019 EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis Chaoqi Wang, Roger Grosse, Sanja Fidler, Guodong Zhang

ICLR 2019 Three Mechanisms of Weight Decay Regularization Guodong Zhang, Chaoqi Wang, Bowen Xu, Roger Grosse

ICML 2018 Differentiable Compositional Kernel Learning for Gaussian Processes Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger Grosse