Neural Variational Hybrid Collaborative Filtering. - Teng Xiao; Shangsong Liang; Hong Shen 001; Zaiqiao Meng (CoRR, 2018)

Bayesian Deep Collaborative Matrix Factorization. - Teng Xiao; Shangsong Liang; Weizhou Shen; Zaiqiao Meng (AAAI, 2019)

Dynamic Collaborative Recurrent Learning. - Teng Xiao; Shangsong Liang; Zaiqiao Meng (CIKM, 2019)

Dynamic Bayesian Metric Learning for Personalized Product Search. - Teng Xiao; Jiaxin Ren; Zaiqiao Meng; Huan Sun 001; Shangsong Liang (CIKM, 2019)

Robustifying Relative Orientations With Respect to Repetitive Structures and Very Short Baselines for Global SfM. - Xin Wang 096; Teng Xiao; Michael Gruber; Christian Heipke (CVPR Workshops, 2019)

ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. - Jing Song; Hong Shen 001; Zijing Ou; Junyi Zhang 001; Teng Xiao; Shangsong Liang (IJCAI, 2019)

Semi-supervisedly Co-embedding Attributed Networks. - Zaiqiao Meng; Shangsong Liang; Jinyuan Fang; Teng Xiao (NeurIPS, 2019)

Neural Variational Matrix Factorization with Side Information for Collaborative Filtering. - Teng Xiao; Hong Shen 001 (PAKDD (1), 2019)

Variational Deep Collaborative Matrix Factorization for Social Recommendation. - Teng Xiao; Hui Tian 001; Hong Shen 001 (PAKDD (1), 2019)

Hierarchical Neural Variational Model for Personalized Sequential Recommendation. - Teng Xiao; Shangsong Liang; Zaiqiao Meng (WWW, 2019)

Neural variational matrix factorization for collaborative filtering in recommendation systems. - Teng Xiao; Hong Shen 001 (Appl. Intell., 2019)

A General Offline Reinforcement Learning Framework for Interactive Recommendation. - Teng Xiao; Donglin Wang (AAAI, 2021)

Learning How to Propagate Messages in Graph Neural Networks. - Teng Xiao; Zhengyu Chen 001; Donglin Wang; Suhang Wang (KDD, 2021)

Progressive Structure from Motion by Iteratively Prioritizing and Refining Match Pairs. - Teng Xiao; Qingsong Yan; Weile Ma; Fei Deng (Remote. Sens., 2021)

Towards Off-Policy Learning for Ranking Policies with Logged Feedback. - Teng Xiao; Suhang Wang (AAAI, 2022)

Representation Matters When Learning From Biased Feedback in Recommendation. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (CIKM, 2022)

BA-GNN: On Learning Bias-Aware Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang (ICDE, 2022)

Decoupled Self-supervised Learning for Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (NeurIPS, 2022)

Towards Unbiased and Robust Causal Ranking for Recommender Systems. - Teng Xiao; Suhang Wang (WSDM, 2022)

Decoupled Self-supervised Learning for Non-Homophilous Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (CoRR, 2022)

Towards Bridging Algorithm and Theory for Unbiased Recommendation. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (CoRR, 2022)

Towards Fair Graph Neural Networks via Graph Counterfactual. - Zhimeng Guo; Jialiang Li 003; Teng Xiao; Yao Ma 001; Suhang Wang (CIKM, 2023)

Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (KDD, 2023)

Certifiably Robust Graph Contrastive Learning. - Minhua Lin; Teng Xiao; Enyan Dai; Xiang Zhang 001; Suhang Wang (NeurIPS, 2023)

Simple and Asymmetric Graph Contrastive Learning without Augmentations. - Teng Xiao; Huaisheng Zhu; Zhengyu Chen 001; Suhang Wang (NeurIPS, 2023)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (CoRR, 2023)

Fairness-aware Message Passing for Graph Neural Networks. - Huaisheng Zhu; Guoji Fu; Zhimeng Guo; Zhiwei Zhang; Teng Xiao; Suhang Wang (CoRR, 2023)

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. - Zhimeng Guo; Jialiang Li 003; Teng Xiao; Yao Ma 001; Suhang Wang (CoRR, 2023)

Learning to Reweight for Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang; Zheqi Lv; Min Zhang 005; Jinluan Yang; Chengqiang Lu; Hongxia Yang; Fei Wu 001 (CoRR, 2023)

Improving knowledge tracing via a heterogeneous information network enhanced by student interactions. - Jia Xu 005; Xinyue Huang; Teng Xiao; Pin Lv (Expert Syst. Appl., 2023)

Learning to Reweight for Generalizable Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang; Zheqi Lv; Min Zhang 005; Jinluan Yang; Chengqiang Lu; Hongxia Yang; Fei Wu 001 (AAAI, 2024)

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (BIBM, 2024)

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective. - Teng Xiao; Mingxiao Li 004; Yige Yuan; Huaisheng Zhu; Chao Cui; Vasant G. Honavar (EMNLP, 2024)

Pareto Graph Self-Supervised Learning. - Zhengyu Chen 001; Teng Xiao; Donglin Wang; Min Zhang 005 (ICASSP, 2024)

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation. - Shiqi Chen; Miao Xiong; Junteng Liu; Zhengxuan Wu; Teng Xiao; Siyang Gao; Junxian He (ICML, 2024)

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. - Teng Xiao; Huaisheng Zhu; Zhiwei Zhang; Zhimeng Guo; Charu C. Aggarwal; Suhang Wang; Vasant G. Honavar (ICML, 2024)

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment. - Teng Xiao; Yige Yuan; Huaisheng Zhu; Mingxiao Li 004; Vasant G. Honavar (NeurIPS, 2024)

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback. - Teng Xiao; Suhang Wang (CoRR, 2024)

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (CoRR, 2024)

MolBind: Multimodal Alignment of Language, Molecules, and Proteins. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (CoRR, 2024)

Discovering Invariant Neighborhood Patterns for Heterophilic Graphs. - Ruihao Zhang; Zhengyu Chen 001; Teng Xiao; Yueyang Wang; Kun Kuang (CoRR, 2024)

MITA: Bridging the Gap between Model and Data for Test-time Adaptation. - Yige Yuan; Bingbing Xu 001; Teng Xiao; Liang Hou; Fei Sun 001; Huawei Shen; Xueqi Cheng (CoRR, 2024)

Fact-Level Confidence Calibration and Self-Correction. - Yige Yuan; Bingbing Xu 001; Hexiang Tan; Fei Sun 001; Teng Xiao; Wei Li 176; Huawei Shen; Xueqi Cheng (CoRR, 2024)

MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. - Qingsong Yan; Junhua Kang; Teng Xiao; Haibing Liu; Fei Deng (Remote. Sens., 2024)

Tracing Human Stress From Physiological Signals Using UWB Radar. - Jia Xu 005; Teng Xiao; Pin Lv; Zhe Chen 015; Chao Cai 001; Yang Zhang 025; Zehui Xiong (IEEE Internet Things J., 2024)

Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies. - Zhengyu Chen 001; Siqi Wang; Teng Xiao; Yudong Wang; Shiqi Chen; Xunliang Cai; Junxian He; Jingang Wang (ACL (1), 2025)

Dialogue-RAG: Enhancing Retrieval for LLMs via Node-Linking Utterance Rewriting. - Qiwei Li 002; Teng Xiao; Zuchao Li; Ping Wang 028; Mengjia Shen; Hai Zhao 001 (ACL (1), 2025)

SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. - Teng Xiao; Yige Yuan; Zhengyu Chen 001; Mingxiao Li 004; Shangsong Liang; Zhaochun Ren; Vasant G. Honavar (ICLR, 2025)

On a Connection Between Imitation Learning and RLHF. - Teng Xiao; Yige Yuan; Mingxiao Li 004; Zhengyu Chen 001; Vasant G. Honavar (ICLR, 2025)

DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (ICLR, 2025)

InfoPO: On Mutual Information Maximization for Large Language Model Alignment. - Teng Xiao; Zhen Ge; Sujay Sanghavi; Tian Wang; Julian Katz-Samuels; Marc Versage; Qingjun Cui; Trishul Chilimbi (NAACL (Long Papers), 2025)

Fact-Level Calibration and Correction for Long-Form Generations. - Yige Yuan; Bingbing Xu 001; Hexiang Tan; Fei Sun 001; Teng Xiao; Wei Li 176; Huawei Shen; Xueqi Cheng (SIGIR, 2025)

Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. - Jinluan Yang; Zhengyu Chen 001; Teng Xiao; Yong Lin; Wenqiao Zhang; Kun Kuang (WWW, 2025)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Zongyu Wu 001; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (Mach. Intell. Res., 2025)

A Deep Single Image Rectification Approach for Pan-Tilt-Zoom Cameras. - Teng Xiao; Qi Hu; Qingsong Yan; Wei Liu; Zhiwei Ye; Fei Deng (CoRR, 2025)

Incentivizing Strong Reasoning from Weak Supervision. - Yige Yuan; Teng Xiao; Shuchang Tao; Xue Wang 010; Jinyang Gao; Bolin Ding; Bingbing Xu 001 (CoRR, 2025)

Inference-time Alignment in Continuous Space. - Yige Yuan; Teng Xiao; Li Yunfan; Bingbing Xu 001; Shuchang Tao; Yunqi Qiu; Huawei Shen; Xueqi Cheng (CoRR, 2025)

From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. - Zhengyu Chen 001; Yudong Wang; Teng Xiao; Ruochen Zhou; Xuesheng Yang; Wei Wang; Zhifang Sui; Jingang Wang (CoRR, 2025)

Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs. - Zhengyu Chen 001; Siqi Wang; Teng Xiao; Yudong Wang; Shiqi Chen; Xunliang Cai; Junxian He; Jingang Wang (CoRR, 2025)

Optimizing Token Choice for Code Watermarking: A RL Approach. - Zhimeng Guo; Huaisheng Zhu; Siyuan Xu; Hangfan Zhang; Teng Xiao; Minhao Cheng (CoRR, 2025)