Compact Object Representation of a Non-Rigid Object for Real-Time Tracking in AR Systems. - Tonghan Wang 001; Xueying Qin; Fan Zhong; Xinmeng Tong; Baoquan Chen; Ming C. Lin (ISMAR Adjunct, 2018)

Convergence of Multi-Agent Learning with a Finite Step Size in General-Sum Games. - Xinliang Song; Tonghan Wang 001; Chongjie Zhang (AAMAS, 2019)

Influence-Based Multi-Agent Exploration. - Tonghan Wang 001; Jianhao Wang; Yi Wu 013; Chongjie Zhang (ICLR, 2020)

Learning Nearly Decomposable Value Functions Via Communication Minimization. - Tonghan Wang 001; Jianhao Wang; Chongyi Zheng; Chongjie Zhang (ICLR, 2020)

ROMA: Multi-Agent Reinforcement Learning with Emergent Roles. - Tonghan Wang 001; Heng Dong 001; Victor R. Lesser; Chongjie Zhang (ICML, 2020)

Incorporating Pragmatic Reasoning Communication into Emergent Language. - Yipeng Kang; Tonghan Wang 001; Gerard de Melo (NeurIPS, 2020)

Off-Policy Multi-Agent Decomposed Policy Gradients. - Yihan Wang; Beining Han; Tonghan Wang 001; Heng Dong 001; Chongjie Zhang (CoRR, 2020)

RODE: Learning Roles to Decompose Multi-Agent Tasks. - Tonghan Wang 001; Tarun Gupta 002; Anuj Mahajan; Bei Peng 001; Shimon Whiteson; Chongjie Zhang (ICLR, 2021)

DOP: Off-Policy Multi-Agent Decomposed Policy Gradients. - Yihan Wang; Beining Han; Tonghan Wang 001; Heng Dong 001; Chongjie Zhang (ICLR, 2021)

Celebrating Diversity in Shared Multi-Agent Reinforcement Learning. - Chenghao Li 002; Tonghan Wang 001; Chengjie Wu; Qianchuan Zhao; Jun Yang 028; Chongjie Zhang (NeurIPS, 2021)

Birds of a Feather Flock Together: A Close Look at Cooperation Emergence via Multi-Agent RL. - Heng Dong 001; Tonghan Wang 001; Jiayuan Liu; Chongjie Zhang (CoRR, 2021)

Containerized Distributed Value-Based Multi-Agent Reinforcement Learning. - Siyang Wu; Tonghan Wang 001; Chenghao Li 002; Chongjie Zhang (CoRR, 2021)

Context-Aware Sparse Deep Coordination Graphs. - Tonghan Wang 001; Liang Zeng 002; Weijun Dong; Qianlan Yang; Yang Yu 001; Chongjie Zhang (ICLR, 2022)

Self-Organized Polynomial-Time Coordination Graphs. - Qianlan Yang; Weijun Dong; Zhizhou Ren; Jianhao Wang; Tonghan Wang 001; Chongjie Zhang (ICML, 2022)

Low-Rank Modular Reinforcement Learning via Muscle Synergy. - Heng Dong 001; Tonghan Wang 001; Jiayuan Liu; Chongjie Zhang (NeurIPS, 2022)

Non-Linear Coordination Graphs. - Yipeng Kang; Tonghan Wang 001; Qianlan Yang; Xiaoran Wu; Chongjie Zhang (NeurIPS, 2022)

Multi-Agent Policy Transfer via Task Relationship Modeling. - Rongjun Qin; Feng Chen 042; Tonghan Wang 001; Lei Yuan 005; Xiaoran Wu; Zongzhang Zhang; Chongjie Zhang; Yang Yu 001 (CoRR, 2022)

Symmetry-Aware Robot Design with Structured Subgroups. - Heng Dong 001; Junyu Zhang; Tonghan Wang 001; Chongjie Zhang (ICML, 2023)

Deep Contract Design via Discontinuous Networks. - Tonghan Wang 001; Paul Duetting; Dmitry Ivanov; Inbal Talgam-Cohen; David C. Parkes (NeurIPS, 2023)

Deep Contract Design via Discontinuous Piecewise Affine Neural Networks. - Tonghan Wang 001; Paul Dütting; Dmitry Ivanov; Inbal Talgam-Cohen; David C. Parkes (CoRR, 2023)

Never Explore Repeatedly in Multi-Agent Reinforcement Learning. - Chenghao Li 002; Tonghan Wang 001; Chongjie Zhang; Qianchuan Zhao (CoRR, 2023)

Multi-Sender Persuasion: A Computational Perspective. - Safwan Hossain; Tonghan Wang 001; Tao Lin 013; Yiling Chen 001; 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 001; Safwan Hossain; Henry Gasztowtt; Stephan Zheng; David C. Parkes; Milind Tambe; Yiling Chen 001 (ICML, 2024)

GemNet: Menu-Based, Strategy-Proof Multi-Bidder Auctions Through Deep Learning. - Tonghan Wang 001; Yanchen Jiang; David C. Parkes (EC, 2024)

Multi-agent policy transfer via task relationship modeling. - Rongjun Qin; Feng Chen 042; Tonghan Wang 001; Lei Yuan 005; Xiaoran Wu; Yipeng Kang; Zongzhang Zhang; Chongjie Zhang; Yang Yu 001 (Sci. China Inf. Sci., 2024)

Social Environment Design. - Edwin Zhang; Sadie Zhao; Tonghan Wang 001; Safwan Hossain; Henry Gasztowtt; Stephan Zheng; David C. Parkes; Milind Tambe; Yiling Chen 001 (CoRR, 2024)

Principal-Agent Reinforcement Learning. - Dima Ivanov; Paul Dütting; Inbal Talgam-Cohen; Tonghan Wang 001; David C. Parkes (CoRR, 2024)

The Bandit Whisperer: Communication Learning for Restless Bandits. - Yunfan Zhao; Tonghan Wang 001; Dheeraj Mysore Nagaraj; Aparna Taneja; Milind Tambe (AAAI, 2025)

On Diffusion Models for Multi-Agent Partial Observability: Shared Attractors, Error Bounds, and Composite Flow. - Tonghan Wang 001; Heng Dong 001; Yanchen Jiang; David C. Parkes; Milind Tambe (AAMAS, 2025)

Robust Optimization with Diffusion Models for Green Security. - Lingkai Kong; Haichuan Wang; Yuqi Pan; Cheol Woo Kim; Mingxiao Song; Alayna Nguyen; Tonghan Wang 001; Haifeng Xu; Milind Tambe (UAI, 2025)

Policy-to-Language: Train LLMs to Explain Decisions with Flow-Matching Generated Rewards. - Xinyi Yang; Liang Zeng 002; Heng Dong 001; Chao Yu; Xiaoran Wu; Huazhong Yang; Yu Wang; Milind Tambe; Tonghan Wang 001 (CoRR, 2025)

BundleFlow: Deep Menus for Combinatorial Auctions by Diffusion-Based Optimization. - Tonghan Wang 001; Yanchen Jiang; David C. Parkes (CoRR, 2025)

Celebrating Diversity With Subtask Specialization in Shared Multiagent Reinforcement Learning. - Chenghao Li 002; Tonghan Wang 001; Chengjie Wu; Qianchuan Zhao; Jun Yang 028; Chongjie Zhang (IEEE Trans. Neural Networks Learn. Syst., 2025)

Adaptive Frontier Exploration on Graphs with Applications to Network-Based Disease Testing. - Davin Choo; Yuqi Pan; Tonghan Wang 001; Milind Tambe; Alastair van Heerden; Cheryl Johnson (CoRR, 2025)

Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data. - Lingkai Kong; Haichuan Wang; Tonghan Wang 001; Guojun Xiong; Milind Tambe (CoRR, 2025)