User Interests Imbalance Exploration in Social Recommendation: A Fitness Adaptation. - Tianchun Wang; Xiaoming Jin; Xuetao Ding; Xiaojun Ye (CIKM, 2014)

Transfer Nonnegative Matrix Factorization for Image Representation. - Tianchun Wang; Tengqi Ye; Cathal Gurrin (MMM (2), 2016)

Learning Multiple Views with Orthogonal Denoising Autoencoders. - Tengqi Ye; Tianchun Wang; Kevin McGuinness; Yu Guo; Cathal Gurrin (MMM (1), 2016)

Multi-Relevance Transfer Learning. - Tianchun Wang (CoRR, 2017)

Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-Grained Air Quality. - Zhongang Qi; Tianchun Wang; Guojie Song; Weisong Hu; Xi Li 001; Zhongfei Zhang (IEEE Trans. Knowl. Data Eng., 2018)

Personalized Federated Learning via Heterogeneous Modular Networks. - Tianchun Wang; Wei Cheng 002; Dongsheng Luo; Wenchao Yu; Jingchao Ni; Liang Tong; Haifeng Chen; Xiang Zhang 001 (ICDM, 2022)

Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial Control Systems. - Xu Zheng 003; Tianchun Wang; Samin Yasar Chowdhury; Ruimin Sun; Dongsheng Luo (EuroS&P Workshops, 2023)

GC-Flow: A Graph-Based Flow Network for Effective Clustering. - Tianchun Wang; Farzaneh Mirzazadeh; Xiang Zhang 001; Jie Chen (ICML, 2023)

DyExplainer: Explainable Dynamic Graph Neural Networks. - Tianchun Wang; Dongsheng Luo; Wei Cheng 002; Haifeng Chen; Xiang Zhang 001 (CoRR, 2023)

Explaining Time Series via Contrastive and Locally Sparse Perturbations. - Zichuan Liu; Yingying Zhang; Tianchun Wang; Zefan Wang; Dongsheng Luo; Mengnan Du; Min Wu 008; Yi Wang 022; Chunlin Chen; Lunting Fan; Qingsong Wen (ICLR, 2024)

Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks. - Xu Zheng 003; Farhad Shirani 001; Tianchun Wang; Wei Cheng 002; Zhuomin Chen; Haifeng Chen; Hua Wei 001; Dongsheng Luo (ICLR, 2024)

Parametric Augmentation for Time Series Contrastive Learning. - Xu Zheng 003; Tianchun Wang; Wei Cheng 002; Aitian Ma; Haifeng Chen; Mo Sha 001; Dongsheng Luo (ICLR, 2024)

TimeX++: Learning Time-Series Explanations with Information Bottleneck. - Zichuan Liu; Tianchun Wang; Jimeng Shi; Xu Zheng 003; Zhuomin Chen; Lei Song 001; Wenqian Dong; Jayantha Obeysekera; Farhad Shirani 001; Dongsheng Luo (ICML, 2024)

Protecting Your LLMs with Information Bottleneck. - Zichuan Liu; Zefan Wang; Linjie Xu; Jinyu Wang; Lei Song 001; Tianchun Wang; Chunlin Chen; Wei Cheng 002; Jiang Bian 002 (NeurIPS, 2024)

PAC Learnability under Explanation-Preserving Graph Perturbations. - Xu Zheng 003; Farhad Shirani 001; Tianchun Wang; Shouwei Gao; Wenqian Dong; Wei Cheng 002; Dongsheng Luo (CoRR, 2024)

Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Models. - Zhawnen Chen; Tianchun Wang; Yizhou Wang 006; Michal Kosinski; Xiang Zhang 001; Yun Fu 001; Sheng Li 001 (CoRR, 2024)

DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. - Weijieying Ren; Tianxiang Zhao 001; Lei Wang 185; Tianchun Wang; Vasant G. Honavar (ACL (Findings), 2025)

Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors. - Tianchun Wang; Yuanzhou Chen; Zichuan Liu; Zhanwen Chen; Haifeng Chen; Xiang Zhang 001; Wei Cheng 002 (ICLR, 2025)

DyExplainer: Self-explainable Dynamic Graph Neural Network with Sparse Attentions. - Tianchun Wang; Dongsheng Luo; Wei Cheng 002; Haifeng Chen; Xiang Zhang 001 (ACM Trans. Knowl. Discov. Data, 2025)

Diversified Sampling Improves Scaling LLM inference. - Tianchun Wang; Zichuan Liu; Yuanzhou Chen; Jonathan Light; Haifeng Chen; Xiang Zhang 001; Wei Cheng 002 (CoRR, 2025)