Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes. - Xin-Qiang Cai; Peng Zhao 006; Kai-Ming Ting; Xin Mu; Yuan Jiang 001 (ICDM, 2019)

Expert-Level Atari Imitation Learning from Demonstrations Only. - Xin-Qiang Cai; Yao-Xiang Ding 001; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2019)

Imitation Learning from Pixel-Level Demonstrations by HashReward. - Xin-Qiang Cai; Yao-Xiang Ding 001; Yuan Jiang 001; Zhi-Hua Zhou (AAMAS, 2021)

Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations. - Xin-Qiang Cai; Yao-Xiang Ding 001; Zi-Xuan Chen; Yuan Jiang 001; Masashi Sugiyama; Zhi-Hua Zhou (CoRR, 2021)

Anomaly Guided Policy Learning from Imperfect Demonstrations. - Zi-Xuan Chen; Xin-Qiang Cai; Yuan Jiang 001; Zhi-Hua Zhou (AAMAS, 2022)

Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning. - Xin-Qiang Cai; Yao-Xiang Ding 001; Zi-Xuan Chen; Yuan Jiang 001; Masashi Sugiyama; Zhi-Hua Zhou (ICLR, 2023)

Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. - Xin-Qiang Cai; Pushi Zhang; Li Zhao 007; Jiang Bian 002; Masashi Sugiyama; Ashley Llorens (NeurIPS, 2023)

Imitation Learning from Vague Feedback. - Xin-Qiang Cai; Yu-Jie Zhang; Chao-Kai Chiang; Masashi Sugiyama (NeurIPS, 2023)

Leveraging Multi-lingual Positive Instances in Contrastive Learning to Improve Sentence Embedding. - Kaiyan Zhao; Qiyu Wu 001; Xin-Qiang Cai; Yoshimasa Tsuruoka (EACL (1), 2024)

An Animation-Based Augmentation Approach for Action Recognition from Discontinuous Video. - Xingyu Song; Zhan Li; Shi Chen 006; Xin-Qiang Cai; Kazuyuki Demachi (ECAI, 2024)

Soft-Label Integration for Robust Toxicity Classification. - Zelei Cheng; Xian Wu 007; Jiahao Yu 001; Shuo Han; Xin-Qiang Cai; Xinyu Xing 001 (NeurIPS, 2024)

Reinforcement Learning from Bagged Reward: A Transformer-based Approach for Instance-Level Reward Redistribution. - Yuting Tang; Xin-Qiang Cai; Yao-Xiang Ding 001; Qiyu Wu 001; Guoqing Liu; Masashi Sugiyama (CoRR, 2024)

Leveraging Domain-Unlabeled Data in Offline Reinforcement Learning across Two Domains. - Soichiro Nishimori; Xin-Qiang Cai; Johannes Ackermann; Masashi Sugiyama (CoRR, 2024)

Beyond Simple Sum of Delayed Rewards: Non-Markovian Reward Modeling for Reinforcement Learning. - Yuting Tang; Xin-Qiang Cai; Jing-Cheng Pang; Qiyu Wu 001; Yao-Xiang Ding 001; Masashi Sugiyama (CoRR, 2024)

Learning View-invariant World Models for Visual Robotic Manipulation. - Jing-Cheng Pang; Nan Tang; Kaiyuan Li; Yuting Tang; Xin-Qiang Cai; Zhen-Yu Zhang; Gang Niu 001; Masashi Sugiyama; Yang Yu 001 (ICLR, 2025)

Reinforcement Learning from Bagged Reward. - Yuting Tang; Xin-Qiang Cai; Yao-Xiang Ding 001; Qiyu Wu 001; Guoqing Liu; Masashi Sugiyama (Trans. Mach. Learn. Res., 2025)

UC-MOA: Utility-Conditioned Multi-Objective Alignment for Distributional Pareto-Optimality. - Zelei Cheng; Xin-Qiang Cai; Yuting Tang; Pushi Zhang; Boming Yang; Xinyu Xing 001 (CoRR, 2025)

PIG-Nav: Key Insights for Pretrained Image Goal Navigation Models. - Jiansong Wan; Chengming Zhou; Jinkua Liu; Xiangge Huang; Xiaoyu Chen; Xiaohan Yi; Qisen Yang; Baiting Zhu; Xin-Qiang Cai; Lixing Liu; Rushuai Yang; Chuheng Zhang; et al. (CoRR, 2025)