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Research Works

	Dyn-O: Building Structured World Models with Object-Centric Representations Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian NeurIPS 2025 arXiv
	What Do Latent Action Models Actually Learn? Chuheng Zhang*, Tim Pearce*, Pushi Zhang, Kaixin Wang, Xiaoyu Chen, Wei Shen, Li Zhao, Jiang Bian NeurIPS 2025 arXiv
	villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models Xiaoyu Chen*, Hangxing Wei*, Pushi Zhang*, Chuheng Zhang*, Kaixin Wang*, Yanjiang Guo, Rushuai Yang, Yucen Wang, Xinquan Xiao, Li Zhao, Jianyu Chen, Jiang Bian arXiv 2025 site  /  arXiv  /  code
	Uncovering Untapped Potential in Sample-Efficient World Model Agents Lior Cohen, Kaixin Wang, Bingyi Kang, Uri Gadot, Shie Mannor arXiv 2025 arXiv  /  code
	How Far is Video Generation from World Model: A Physical Law Perspective Bingyi Kang*, Yang Yue*, Rui Lu, Zhijie Lin, Yang Zhao, Kaixin Wang, Gao Huang, Jiashi Feng ICML 2025 site  /  arXiv  /  code
	Implicit Curriculum in Procgen Made Explicit Zhenxiong Tan*, Kaixin Wang*, Xinchao Wang NeurIPS 2024 (spotlight) code
	Improving Token-Based World Models with Parallel Observation Prediction Lior Cohen, Kaixin Wang, Bingyi Kang, Shie Mannor ICML 2024 arXiv  /  code
	Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel Uri Gadot*, Kaixin Wang*, Navdeep Kumar, Kfir Y. Levy, Shie Mannor ICML 2024 arXiv  /  code
	Efficient Value Iteration for s-rectangular Robust Markov Decision Processes Navdeep Kumar, Kaixin Wang, Kfir Y. Levy, Shie Mannor ICML 2024 arXiv
	PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient Kaixin Wang, Daquan Zhou, Jiashi Feng, Shie Mannor ICML 2023
	Reachability-Aware Laplacian Representation in Reinforcement Learning Kaixin Wang*, Kuangqi Zhou*, Jiashi Feng, Bryan Hooi, Xinchao Wang ICML 2023 arXiv
	Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments Kaixin Wang, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan ICLR 2023
	Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang LoG 2022
	Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang NeurIPS 2022 arXiv
	Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction Kuangqi Zhou, Kaixin Wang, Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang arXiv 2022 arXiv
	Policy Gradient for Reinforcement Learning with General Utilities Navdeep Kumar, Kaixin Wang, Kfir Levy, Shie Mannor RLDM 2022 arXiv
	The Geometry of Robust Value Functions Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor ICML 2022 arXiv  /  presentation
	Understanding and Resolving Performance Degradation in Graph Convolutional Networks Kuangqi Zhou*, Yanfei Dong*, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng CIKM 2021 arXiv  /  code  /  presentation
	Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing Kaixin Wang*, Kuangqi Zhou*, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng ICML 2021 arXiv  /  code (coming soon)  /  presentation
	Improving Generalization in Reinforcement Learning with Mixture Regularization Kaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng NeurIPS 2020 arXiv  /  code  /  site  /  presentation
	Neural Epitome Search for Architecture-Agnostic Network Compression Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang, Jianchao Yang, Jiashi Feng ICLR 2020 arXiv  /  code  /  presentation
	PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment Kaixin Wang, Jun Hao Liew, Yingtian Zou, Daquan Zhou, Jiashi Feng ICCV 2019 (oral) arXiv  /  code  /  presentation