Wang, Tonghan

23 publications

ICLR 2026 Translate Policy to Language: Flow Matching Generated Rewards for LLM Explanations Xinyi Yang, Liang Zeng, Heng Dong, Chao Yu, Xiaoran Wu, Huazhong Yang, Yu Wang, Milind Tambe, Tonghan Wang

NeurIPS 2025 Adaptive Frontier Exploration on Graphs with Applications to Network-Based Disease Testing Davin Choo, Yuqi Pan, Tonghan Wang, Milind Tambe, Alastair van Heerden, Cheryl Johnson

NeurIPS 2025 BundleFlow: Deep Menus for Combinatorial Auctions by Diffusion-Based Optimization Tonghan Wang, Yanchen Jiang, David C. Parkes

NeurIPS 2025 Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data Lingkai Kong, Haichuan Wang, Tonghan Wang, Guojun Xiong, Milind Tambe

UAI 2025 Robust Optimization with Diffusion Models for Green Security Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe

AAAI 2025 The Bandit Whisperer: Communication Learning for Restless Bandits Yunfan Zhao, Tonghan Wang, Dheeraj Mysore Nagaraj, Aparna Taneja, Milind Tambe

ICML 2024 Multi-Sender Persuasion: A Computational Perspective Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, Haifeng Xu

ICML 2024 Position: Social Environment Design Should Be Further Developed for AI-Based Policy-Making Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen

NeurIPS 2023 Deep Contract Design via Discontinuous Networks Tonghan Wang, Paul Duetting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes

ICML 2023 Symmetry-Aware Robot Design with Structured Subgroups Heng Dong, Junyu Zhang, Tonghan Wang, Chongjie Zhang

ICLR 2022 Context-Aware Sparse Deep Coordination Graphs Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang

NeurIPS 2022 Low-Rank Modular Reinforcement Learning via Muscle Synergy Heng Dong, Tonghan Wang, Jiayuan Liu, Chongjie Zhang

NeurIPSW 2022 Model and Method: Training-Time Attack for Cooperative Multi-Agent Reinforcement Learning Siyang Wu, Tonghan Wang, Xiaoran Wu, Jingfeng Zhang, Yujing Hu, Changjie Fan, Chongjie Zhang

NeurIPSW 2022 Multi-Agent Policy Transfer via Task Relationship Modeling Rong-Jun Qin, Feng Chen, Tonghan Wang, Lei Yuan, Xiaoran Wu, Yipeng Kang, Zongzhang Zhang, Chongjie Zhang, Yang Yu

NeurIPS 2022 Non-Linear Coordination Graphs Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang

ICML 2022 Self-Organized Polynomial-Time Coordination Graphs Qianlan Yang, Weijun Dong, Zhizhou Ren, Jianhao Wang, Tonghan Wang, Chongjie Zhang

NeurIPS 2021 Celebrating Diversity in Shared Multi-Agent Reinforcement Learning Chenghao Li, Tonghan Wang, Chengjie Wu, Qianchuan Zhao, Jun Yang, Chongjie Zhang

ICLR 2021 DOP: Off-Policy Multi-Agent Decomposed Policy Gradients Yihan Wang, Beining Han, Tonghan Wang, Heng Dong, Chongjie Zhang

ICLR 2021 RODE: Learning Roles to Decompose Multi-Agent Tasks Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang

NeurIPS 2020 Incorporating Pragmatic Reasoning Communication into Emergent Language Yipeng Kang, Tonghan Wang, Gerard de Melo

ICLR 2020 Influence-Based Multi-Agent Exploration Tonghan Wang, Jianhao Wang, Yi Wu, Chongjie Zhang

ICLR 2020 Learning Nearly Decomposable Value Functions via Communication Minimization Tonghan Wang, Jianhao Wang, Chongyi Zheng, Chongjie Zhang

ICML 2020 ROMA: Multi-Agent Reinforcement Learning with Emergent Roles Tonghan Wang, Heng Dong, Victor Lesser, Chongjie Zhang