Xiangxin Zhou
I work on LLM RL at Tencent HY.
My research focuses on LLM RL and agents — the engine (principled algorithms that scale), the loop (intelligence that improves itself), and the interface (agents that act on the world).
I received my B.E. in Tsinghua University in 2021, and my Ph.D. in Institute of Automation, Chinese Academy of Sciences (CASIA) and University of Chinese Academy of Sciences (UCAS) in 2026, under the supervision of Liang Wang.
I have interned at Tencent Hunyuan LLM, Tencent Hunyuan Multimodal, Sea AI Lab, Xiaohongshu Hi Lab, ByteDance Seed, ByteDance AI Lab, and ByteDance AML.
Publications
* Equal Contribution † Project Lead # Corresponding Author
SceneActBench: Can Agents Act on the 3D Scenes They See?
Yifei Zhao*, Xiangxin Zhou*#, Wenhao Yang*, Jiaqi Tang*, Pu Jian*, Huanjin Yao*, Jiarui Yao*, Haowei Lin, Chunchao Guo, Zhuo Chen, Wenkai Lyu, Jianzhu Ma, Xueqian Wang, Wenxi Zhu#
arXiv Preprint, 2026
Stale but Stable: Staleness-Adaptive Trust Regions for Stabilizing Asynchronous Reinforcement Learning
Junyao Yang#, Yucheng Shi†, Zongxia Li, Zhongzhi Li, Ruhan Wang, Xiangxin Zhou, Kishan Panaganti, Haitao Mi, Leowei Liang
arXiv Preprint, 2026
MeanFlowNFT: Bringing Forward-Process RL to Average-Velocity Generators
Yushi Huang*, Xiangxin Zhou*#, Jun Zhang, Liefeng Bo, Tianyu Pang#
arXiv Preprint, 2026
Predictive Divergence Masks for LLM RL
Xiangxin Zhou*, Jiarui Yao*, Penghui Qi*, Bowen Ping, Jiaqi Tang, Haonan Wang, Tianyu Pang#
arXiv Preprint, 2026
TempAct: Advancing Temporal Plausibility in Autoregressive Video Generation via Planner-Executor RL
Jing Wang*, Xiangxin Zhou*, Jiajun Liang†, Kaiqi Liu, Wanyuan Pang, Zhenyu Xie, Tianyu Pang#, Xiaodan Liang#
arXiv Preprint, 2026
Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models
Bowen Ping*, Xiangxin Zhou*†, Penghui Qi, Minnan Luo#, Liefeng Bo, Tianyu Pang#
arXiv Preprint, 2026
Exploring the Design Space of Reward Backpropagation for Flow Matching
Ruoyu Wang*, Boye Niu*, Xiangxin Zhou*†#, Yushi Huang, Tongliang Liu, Chi Zhang#
arXiv Preprint, 2026
Beyond Uniform Token-Level Trust Region in LLM Reinforcement Learning
Renjie Mao*, Xiangxin Zhou*#, Lvfang Tao*#, Yixin Ding, Yu Shi, Yongguang Lin, Yuheng Wu, Honglin Zhu, Qian Qiu, Wenxi Zhu#
arXiv Preprint, 2026
Rethinking the Divergence Regularization in LLM RL
Jiarui Yao*, Xiangxin Zhou*†, Penghui Qi*†, Wee Sun Lee, Liefeng Bo, Tianyu Pang#
arXiv Preprint, 2026
Disentangled Diffusion Model for 3D Molecular Generation with Protein-Ligand Interaction Priors
Zhilin Huang, Ling Yang, Chujun Qin, Yifei Xing, Hongyang Yu, Xiangxin Zhou, Bing Zheng, Yu Wang, Xin Gao, Wenming Yang#
Bioinformatics, 2026
Reinforcing Few-step Generators via Reward-Tilted Distribution Matching
Yushi Huang*, Xiangxin Zhou*†, Ruoyu Wang*, Chi Zhang, Jun Zhang, Tianyu Pang#
arXiv Preprint, 2026
Rethinking the Trust Region in LLM Reinforcement Learning
Penghui Qi*#, Xiangxin Zhou*, Zichen Liu, Tianyu Pang, Chao Du, Min Lin, Wee Sun Lee#
International Conference on Machine Learning (ICML), 2026
Variational Reasoning for Language Models
Xiangxin Zhou*, Zichen Liu, Haonan Wang, Chao Du, Min Lin, Chongxuan Li, Liang Wang, Tianyu Pang*#
International Conference on Learning Representations (ICLR), 2026
Reinforcing General Reasoning Without Verifiers
Xiangxin Zhou*, Zichen Liu*, Anya Sims*, Haonan Wang, Tianyu Pang, Chongxuan Li, Liang Wang, Min Lin, Chao Du#
International Conference on Learning Representations (ICLR), 2026
GEM: A Gym for Agentic LLMs
Zichen Liu*, Anya Sims*, Keyu Duan*, Changyu Chen*, Simon Yu, Xiangxin Zhou, Haotian Xu, Shaopan Xiong, Bo Liu, Chenmien Tan, Chuen Yang Beh, Weixun Wang, Hao Zhu, Weiyan Shi, Diyi Yang, Michael Shieh, Yee Whye Teh, Wee Sun Lee, Min Lin
International Conference on Learning Representations (ICLR), 2026
h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network
Yanru Qu*, Yijie Zhang*, Wenjuan Tan, Xiangzhe Kong, Xiangxin Zhou, Chaoran Cheng, Mathieu Blanchette, Jiaxuan You, Ge Liu#
International Conference on Learning Representations (ICLR), 2026
Defeating the Training-Inference Mismatch via FP16
Penghui Qi*†, Zichen Liu*, Xiangxin Zhou*, Tianyu Pang, Chao Du, Wee Sun Lee, Min Lin
arXiv Preprint, 2025
Fine-tuning Flow Matching Generative Models with Intermediate Feedback
Jiajun Fan, Chaoran Cheng, Shuaike Shen, Xiangxin Zhou, Ge Liu
arXiv Preprint, 2025
ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
Dong Han*, Zhehong Ai*, Pengxiang Cai*, Shanya Lu, Jianpeng Chen, Zihao Ye, Shuzhou Sun, Ben Gao, Lingli Ge, Weida Wang, Xiangxin Zhou, Xihui Liu, Mao Su, Wanli Ouyang, Lei Bai, Dongzhan Zhou, Tao Xu#, Yuqiang Li#, Shufei Zhang#
arXiv Preprint, 2025
Riemannian Consistency Model
Chaoran Cheng*#, Yusong Wang*, Yuxin Chen, Xiangxin Zhou, Nanning Zheng, Ge Liu
Conference on Neural Information Processing Systems (NeurIPS), 2025
Decomposed Direct Preference Optimization for Structure-Based Drug Design
Xiwei Cheng*, Xiangxin Zhou*, Yu Bao, Yuwei Yang, Quanquan Gu#
Transactions on Machine Learning Research (TMLR), 2025
OS Agents: A Survey on MLLM-based Agents for Computer, Phone and Browser Use
Xueyu Hu†, Tao Xiong, Biao Yi, Zishu Wei, Ruixuan Xiao, Yurun Chen, Jiasheng Ye, Meiling Tao, Xiangxin Zhou, Ziyu Zhao, Yuhuai Li, Shengze Xu, Shenzhi Wang, Xinchen Xu, Shuofei Qiao, Zhaokai Wang, Kun Kuang, Tieyong Zeng, Liang Wang, Jiwei Li, Yuchen Eleanor Jiang, Wangchunshu Zhou, Guoyin Wang, Keting Yin, Zhou Zhao, Hongxia Yang, Fan Wu, Shengyu Zhang#, Fei Wu
Annual Meeting of the Association for Computational Linguistics (ACL), 2025 (Oral)
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou*, Mingyu Li*, Yi Xiao, Jiahan Li, Dongyu Xue, Zaixiang Zheng, Jianzhu Ma, Quanquan Gu#
International Conference on Machine Learning (ICML), 2025
Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training
Minghao Xu, Jiaze Song, Keming Wu, Xiangxin Zhou, Bin Cui, Wentao Zhang#
International Conference on Machine Learning (ICML), 2025
An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen*, Dongyu Xue*†, Xiangxin Zhou, Zaixiang Zheng, Xiangxiang Zeng, Quanquan Gu#
International Conference on Machine Learning (ICML), 2025
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou*, Yi Xiao*, Haowei Lin, Xinheng He, Jiaqi Guan, Yang Wang, Qiang Liu, Feng Zhou, Liang Wang, Jianzhu Ma#
International Conference on Learning Representations (ICLR), 2025
Group Ligands Docking to Protein Pockets
Jiaqi Guan*, Jiahan Li*, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma
International Conference on Learning Representations (ICLR), 2025
ProteinBench: A Holistic Evaluation of Protein Foundation Models
Fei Ye*, Zaixiang Zheng*, Dongyu Xue*, Yuning Shen*, Lihao Wang*, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, Quanquan Gu#
International Conference on Learning Representations (ICLR), 2025
UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
Ruifeng Li, Mingqian Li, Wei Liu, Yuhua Zhou, Xiangxin Zhou, Yuan Yao, Qiang Zhang, Hongyang Chen
International Conference on Learning Representations (ICLR), 2025 (Spotlight)
Binding-Adaptive Diffusion Models for Structure-Based Drug Design
Zhilin Huang*, Ling Yang*, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang#, Wenming Yang#
AAAI Conference on Artificial Intelligence (AAAI), 2024
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery
Ruifeng Li, Wei Liu, Xiangxin Zhou, Mingqian Li, Qiang Zhang, Hongyang Chen, Xuemin Lin
arXiv Preprint, 2024
Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design
Xiangxin Zhou, Jiaqi Guan, Yijia Zhang, Xingang Peng, Liang Wang, Jianzhu Ma#
Conference on Neural Information Processing Systems (NeurIPS), 2024
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
Xiangxin Zhou*, Dongyu Xue*, Ruizhe Chen*, Zaixiang Zheng, Liang Wang, Quanquan Gu#
Conference on Neural Information Processing Systems (NeurIPS), 2024
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou#
International Conference on Machine Learning (ICML), 2024
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
Zhilin Huang*, Ling Yang*, Xiangxin Zhou, Chujun Qin, Yijie Yu, Xiawu Zheng, Zikun Zhou, Wentao Zhang, Yu Wang#, Wenming Yang#
International Conference on Machine Learning (ICML), 2024
Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule
Yi Xiao*, Xiangxin Zhou*, Qiang Liu#, Liang Wang
arXiv Preprint, 2024
Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou*, Xiwei Cheng*, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu#
International Conference on Learning Representations (ICLR), 2024
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
Zhilin Huang*, Ling Yang*, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang#, Bin Cui, Wenming Yang#
International Conference on Learning Representations (ICLR), 2024
GSLB: The Graph Structure Learning Benchmark
Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu#, Shu Wu, Liang Wang, Jeffrey Xu Yu#
Conference on Neural Information Processing Systems (NeurIPS), 2023
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design
Jiaqi Guan*, Xiangxin Zhou*#, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu#
International Conference on Machine Learning (ICML), 2023
A Study of Using Synthetic Data for Effective Association Knowledge Learning
Yuchi Liu, Zhongdao Wang, Xiangxin Zhou, Liang Zheng#
Machine Intelligence Research (MIR), 2023
Semantics-Aware Hidden Markov Model for Human Mobility
Hongzhi Shi, Yong Li, Hancheng Cao, Xiangxin Zhou, Chao Zhang, Vassilis Kostakos
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
Shorter version accepted by SDM
Shorter version accepted by SDM
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu
Conference on Neural Information Processing Systems (NeurIPS), 2019
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, Gang Yu
Technical Report, 2019
Winner of CVPR 2019 WAD NuScenes Challenge
Winner of CVPR 2019 WAD NuScenes Challenge