Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. - Yudi Zhang 007; Yali Du 001; Biwei Huang; Ziyan Wang; Jun Wang 012; Meng Fang; Mykola Pechenizkiy (NeurIPS, 2023)

COOM: A Game Benchmark for Continual Reinforcement Learning. - Tristan Tomilin; Meng Fang; Yudi Zhang 007; Mykola Pechenizkiy (NeurIPS, 2023)

GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning. - Yudi Zhang 007; Yali Du 001; Biwei Huang; Ziyan Wang; Jun Wang 012; Meng Fang; Mykola Pechenizkiy (CoRR, 2023)

Large Language Models Are Neurosymbolic Reasoners. - Meng Fang; Shilong Deng; Yudi Zhang 007; Zijing Shi; Ling Chen 006; Mykola Pechenizkiy; Jun Wang 012 (AAAI, 2024)

Large Action Models: From Inception to Implementation. - Lu Wang 029; Fangkai Yang; Chaoyun Zhang; Junting Lu; Jiaxu Qian; Shilin He; Pu Zhao 004; Bo Qiao 001; Ray Huang; Si Qin; Qisheng Su; Jiayi Ye; et al. (CoRR, 2024)

RuAG: Learned-rule-augmented Generation for Large Language Models. - Yudi Zhang 007; Pei Xiao 007; Lu Wang 029; Chaoyun Zhang; Meng Fang; Yali Du 001; Yevgeniy Puzyrev; Randolph Yao; Si Qin; Qingwei Lin; Mykola Pechenizkiy; Dongmei Zhang 001; et al. (ICLR, 2025)

MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment. - Ziyan Wang; Yali Du 001; Yudi Zhang 007; Meng Fang; Biwei Huang (Trans. Mach. Learn. Res., 2025)

Large Action Models: From Inception to Implementation. - Lu Wang 029; Fangkai Yang; Chaoyun Zhang; Junting Lu; Jiaxu Qian; Shilin He; Pu Zhao 004; Bo Qiao 001; He Huang; Si Qin; Qisheng Su; Jiayi Ye; et al. (Trans. Mach. Learn. Res., 2025)

Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones? - Yudi Zhang 007; Lu Wang 029; Meng Fang; Yali Du 001; Chenghua Huang; Jun Wang; Qingwei Lin; Mykola Pechenizkiy; Dongmei Zhang 001; Saravan Rajmohan; Qi Zhang 066 (CoRR, 2025)