Dual-Curriculum Teacher for Domain-Inconsistent Object Detection in Autonomous Driving. - Longhui Yu; Yifan Zhang 004; Lanqing Hong; Fei Chen 013; Zhenguo Li (BMVC, 2022)

Memory Replay with Data Compression for Continual Learning. - Liyuan Wang; Xingxing Zhang 001; Kuo Yang; Longhui Yu; Chongxuan Li; Lanqing Hong; Shifeng Zhang; Zhenguo Li; Yi Zhong; Jun Zhu 001 (ICLR, 2022)

Multi-Teacher Knowledge Distillation for Incremental Implicitly-Refined Classification. - Longhui Yu; Zhenyu Weng; Yuqing Wang; Yuesheng Zhu (ICME, 2022)

DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality. - Yuqing Wang; Yizhi Wang; Longhui Yu; Yuesheng Zhu; Zhouhui Lian (CVPR, 2023)

Style Expansion Without Forgetting for Handwritten Character Recognition. - Jie Ruan; Zhenyu Weng; Jian Zhang; Yuqing Wang; Longhui Yu; Qiankun Gao; Yuesheng Zhu (ICANN (3), 2023)

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. - Weiyang Liu; Longhui Yu; Adrian Weller; Bernhard Schölkopf (ICLR, 2023)

ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis. - Shoukang Hu; Kaichen Zhou; Kaiyu Li; Longhui Yu; Lanqing Hong; Tianyang Hu; Zhenguo Li; Gim Hee Lee; Ziwei Liu 002 (CoRR, 2023)

Forward-Backward Reasoning in Large Language Models for Verification. - Weisen Jiang; Han Shi; Longhui Yu; Zhengying Liu; Yu Zhang 006; Zhenguo Li; James T. Kwok (CoRR, 2023)

Continual Learning by Modeling Intra-Class Variation. - Longhui Yu; Tianyang Hu; Lanqing Hong; Zhen Liu 019; Adrian Weller; Weiyang Liu (Trans. Mach. Learn. Res., 2023)

Forward-Backward Reasoning in Large Language Models for Mathematical Verification. - Weisen Jiang; Han Shi; Longhui Yu; Zhengying Liu; Yu Zhang 006; Zhenguo Li; James T. Kwok (ACL (Findings), 2024)

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. - Weiyang Liu; Zeju Qiu; Yao Feng 001; Yuliang Xiu; Yuxuan Xue; Longhui Yu; Haiwen Feng; Zhen Liu 019; Juyeon Heo; Songyou Peng; Yandong Wen; Michael J. Black; et al. (ICLR, 2024)

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. - Longhui Yu; Weisen Jiang; Han Shi; Jincheng Yu; Zhengying Liu; Yu Zhang 006; James T. Kwok; Zhenguo Li; Adrian Weller; Weiyang Liu (ICLR, 2024)

Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision. - Zhiqing Sun; Longhui Yu; Yikang Shen; Weiyang Liu; Yiming Yang; Sean Welleck; Chuang Gan 001 (NeurIPS, 2024)

PatentAgent: Intelligent Agent for Automated Pharmaceutical Patent Analysis. - Xin Wang; Yifan Zhang; Xiaojing Zhang; Longhui Yu; Xinna Lin; Jindong Jiang; Bin Ma; Kaicheng Yu (CoRR, 2024)

Towards A Better Initial Policy Model For Scalable Long-CoT Reinforcement Learning. - Bofei Gao; Yejie Wang; Yibo Miao; Ruoyu Wu; Feifan Song 001; Longhui Yu; Tianyu Liu 001; Baobao Chang (ACL (Findings), 2025)

Kimi k1.5: Scaling Reinforcement Learning with LLMs. - Kimi Team; Angang Du; Bofei Gao; Bowei Xing; Changjiu Jiang; Cheng Chen; Cheng Li; Chenjun Xiao; Chenzhuang Du; Chonghua Liao; Chuning Tang; Congcong Wang; et al. (CoRR, 2025)

Kimi-VL Technical Report. - Angang Du; Bohong Yin; Bowei Xing; Bowen Qu; Bowen Wang; Cheng Chen; Chenlin Zhang; Chenzhuang Du; Chu Wei; Congcong Wang; Dehao Zhang; Dikang Du; et al. (CoRR, 2025)

Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning. - Haiming Wang; Mert Unsal; Xiaohan Lin; Mantas Baksys; Junqi Liu; Marco Dos Santos; Flood Sung; Marina Vinyes; Zhenzhe Ying; Zekai Zhu; Jianqiao Lu; Hugues de Saxcé; et al. (CoRR, 2025)