Adapting Generic Features to A Specific Task: A Large Discrepancy Knowledge Distillation for Image Anomaly Detection. - Chenkai Zhang; Tianqi Du; Yueming Wang (BMVC, 2023)

A Message Passing Perspective on Learning Dynamics of Contrastive Learning. - Yifei Wang 001; Qi Zhang 067; Tianqi Du; Jiansheng Yang; Zhouchen Lin; Yisen Wang 001 (ICLR, 2023)

ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond. - Xiaojun Guo; Yifei Wang 001; Tianqi Du; Yisen Wang 001 (ICLR, 2023)

ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. - Xuyang Zhao; Tianqi Du; Yisen Wang 001; Jun Yao; Weiran Huang 001 (ICLR, 2023)

An Improved Graph Convolutional Neural Network based on Graph Auto-encoder. - Dongqi Wang 001; Tianqi Du; Zhongwu Liu; Dongming Chen; Tao Ren 002 (ICCAE, 2024)

On the Role of Discrete Tokenization in Visual Representation Learning. - Tianqi Du; Yifei Wang 001; Yisen Wang 001 (ICLR, 2024)

Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining. - Qi Zhang 067; Tianqi Du; Haotian Huang; Yifei Wang 001; Yisen Wang 001 (ICML, 2024)

When More is Less: Understanding Chain-of-Thought Length in LLMs. - Yuyang Wu; Yifei Wang 001; Tianqi Du; Stefanie Jegelka; Yisen Wang 001 (CoRR, 2025)

Advancing LLM Safe Alignment with Safety Representation Ranking. - Tianqi Du; Zeming Wei; Quan Chen; Chenheng Zhang; Yisen Wang 001 (CoRR, 2025)

Long-Short Alignment for Effective Long-Context Modeling in LLMs. - Tianqi Du; Haotian Huang; Yifei Wang 001; Yisen Wang 001 (CoRR, 2025)