| Neural Variational Hybrid Collaborative Filtering T Xiao, S Liang, H Shen, Z Meng arXiv preprint arXiv:1810.05376, 2018 | 65* | 2018 |
| A General Offline Reinforcement Learning Framework for Interactive Recommendation T Xiao, D Wang The Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021 | 60 | 2021 |
| Learning How to Propagate Messages in Graph Neural Networks T Xiao, Z Chen, D Wang, S Wang ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021 | 53 | 2021 |
| ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. J Song, H Shen, Z Ou, J Zhang, T Xiao, S Liang International Joint Conferences on Artificial Intelligence, 2019 | 39 | 2019 |
| Ba-gnn: On Learning Bias-aware Graph Neural Network Z Chen, T Xiao*, K Kuang 2022 IEEE 38th International Conference on Data Engineering (ICDE), 3012-3024, 2022 | 36 | 2022 |
| Decoupled Self-supervised Learning for Non-Homophilous Graphs T Xiao, Z Chen, Z Guo, Z Zhuang, S Wang NeurIPS 2022, 2022 | 33* | 2022 |
| Semi-supervisedly Co-embedding Attributed Networks Z Meng, S Liang, J Fang, T Xiao NeurIPS 2019, 2019 | 32 | 2019 |
| Hierarchical Neural Variational Model for Personalized Sequential Recommendation T Xiao, S Liang, Z Meng The World Wide Web Conference (WWW), 2019 | 30 | 2019 |
| Dynamic Bayesian Metric Learning for Personalized Product Search T Xiao, J Ren, Z Meng, H Sun, S Liang ACM International Conference on Information and Knowledge Management, 2019 | 22 | 2019 |
| Bayesian Deep Collaborative Matrix Factorization T Xiao, S Liang, W Shen, Z Meng The Thirty-Third AAAI Conference on Artificial Intelligence, 2019 | 21 | 2019 |
| Towards Unbiased and Robust Causal Ranking for Recommender Systems T Xiao, S Wang ACM International Conference on Web Search and Data Mining, 2022 | 16 | 2022 |
| Counterfactual learning on graphs: A survey Z Guo, T Xiao, Z Wu, C Aggarwal, H Liu, S Wang arXiv preprint arXiv:2304.01391, 2023 | 10 | 2023 |
| Dynamic Collaborative Recurrent Learning T Xiao, S Liang, Z Meng ACM International Conference on Information and Knowledge Management, 2019 | 10 | 2019 |
| Representation Matters When Learning from Biased Feedback in Recommendation T Xiao, Z Chen, S Wang ACM International Conference on Information & Knowledge Management, 2022 | 9 | 2022 |
| Towards Fair Graph Neural Networks via Graph Counterfactual Z Guo, J Li, T Xiao, Y Ma, S Wang ACM International Conference on Information and Knowledge Management, 2023 | 5 | 2023 |
| Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective T Xiao, Z Chen, S Wang KDD 2023, 2023 | 5* | 2023 |
| Fairness-aware Message Passing for Graph Neural Networks H Zhu, G Fu, Z Guo, Z Zhang, T Xiao, S Wang arXiv preprint arXiv:2306.11132, 2023 | 5 | 2023 |
| Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback T Xiao, S Wang arXiv preprint arXiv:2401.08959, 2021 | 5* | 2021 |
| Certifiably Robust Graph Contrastive Learning M Lin, T Xiao, E Dai, X Zhang, S Wang NeurIPS 2023, 2023 | 2 | 2023 |
| 3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs H Zhu, T Xiao, VG Honavar arXiv preprint arXiv:2403.07179, 2024 | 1 | 2024 |
