MoE-I²: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition. - Cheng Yang 013; Yang Sui; Jinqi Xiao; Lingyi Huang; Yu Gong; Yuanlin Duan; Wenqi Jia 003; Miao Yin; Yu Cheng; Bo Yuan 001 (EMNLP (Findings), 2024)

Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning. - Yuanlin Duan; Guofeng Cui; He Zhu 001 (NeurIPS, 2024)

Learning World Models for Unconstrained Goal Navigation. - Yuanlin Duan; Wensen Mao; He Zhu 001 (NeurIPS, 2024)

MoE-I2: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition. - Cheng Yang 013; Yang Sui; Jinqi Xiao; Lingyi Huang; Yu Gong; Yuanlin Duan; Wenqi Jia 003; Miao Yin; Yu Cheng; Bo Yuan 001 (CoRR, 2024)

Crop sample prediction and early mapping based on historical data: Exploration of an explainable FKAN framework. - Feifei Cheng; Bingwen Qiu; Peng Yang 005; Wenbin Wu; Qiangyi Yu; Jianping Qian; Bingfang Wu; Jin Chen; Xuehong Chen; Francesco N. Tubiello; Piotr Tryjanowski; Viktoria Takacs; et al. (Comput. Electron. Agric., 2025)