Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge. - Xiu-Shen Wei; Yu-Yan Xu; Yazhou Yao; Jia Wei; Si Xi; Wenyuan Xu; Weidong Zhang; Xiaoxin Lv; Dengpan Fu; Qing Li; Baoying Chen; Haojie Guo; et al. (CoRR, 2020)

Webly-Supervised Fine-Grained Recognition with Partial Label Learning. - Yu-Yan Xu; Yang Shen; Xiu-Shen Wei; Jian Yang 003 (IJCAI, 2022)

Imitator Learning: Achieve Out-of-the-Box Imitation Ability in Variable Environments. - Xiong-Hui Chen; Junyin Ye; Hang Zhao; Yi-Chen Li 001; Haoran Shi; Yu-Yan Xu; Zhihao Ye; Si-Hang Yang; Anqi Huang; Kai Xu 004; Zongzhang Zhang; Yang Yu 001 (CoRR, 2023)

CAT: a coarse-to-fine attention tree for semantic change detection. - Xiu-Shen Wei; Yu-Yan Xu; Chen-Lin Zhang; Gui-Song Xia; Yuxin Peng (Vis. Intell., 2023)

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration. - Xiong-Hui Chen; Junyin Ye; Hang Zhao; Yi-Chen Li 001; XuHui Liu; Haoran Shi; Yu-Yan Xu; Zhihao Ye; Si-Hang Yang; Yang Yu 001; Anqi Huang; Kai Xu 004; et al. (ICML, 2024)

Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning. - Haoxin Lin; Yu-Yan Xu; Yihao Sun; Zhilong Zhang; Yi-Chen Li 001; Chengxing Jia; Junyin Ye; Jiaji Zhang; Yang Yu 001 (ICLR, 2025)