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

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

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

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

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

Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design. - Heng Dong 001; Junyu Zhang; Chongjie Zhang (ICLR, 2024)

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)

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)