| 2025 | ICLR | Regularizing Energy among Training Samples for Out-of-Distribution Generalization. | Yiting Chen, Qitian Wu, Junchi Yan |
| 2025 | ICLR | SLMRec: Distilling Large Language Models into Small for Sequential Recommendation. | Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Yunxiao Shi, Wenfang Lin, Yongfeng Zhang |
| 2025 | ICLR | DiffPuter: Empowering Diffusion Models for Missing Data Imputation. | Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu |
| 2025 | ICML | Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning. | Yang Li, Jiale Ma, Yebin Yang, Qitian Wu, Hongyuan Zha, Junchi Yan |
| 2025 | ICML | Supercharging Graph Transformers with Advective Diffusion. | Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Michael M. Bronstein |
| 2025 | ICML | TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data. | Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu |
| 2024 | AAAI | TDeLTA: A Light-Weight and Robust Table Detection Method Based on Learning Text Arrangement. | Yang Fan, Xiangping Wu, Qingcai Chen, Heng Li, Yan Huang, Zhixiang Cai, Qitian Wu |
| 2024 | CIKM | InfoMLP: Unlocking the Potential of MLPs for Semi-Supervised Learning with Structured Data. | Hengrui Zhang, Qitian Wu, Chenxiao Yang, Philip S. Yu |
| 2024 | ICML | Graph Out-of-Distribution Detection Goes Neighborhood Shaping. | Tianyi Bao, Qitian Wu, Zetian Jiang, Yiting Chen, Jiawei Sun, Junchi Yan |
| 2024 | ICML | Learning Divergence Fields for Shift-Robust Graph Representations. | Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan |
| 2024 | ICML | How Graph Neural Networks Learn: Lessons from Training Dynamics. | Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan |
| 2024 | KDD | GeoMix: Towards Geometry-Aware Data Augmentation. | Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan |
| 2024 | WWW | Graph Out-of-Distribution Generalization via Causal Intervention. | Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan |
| 2024 | WWW | Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions. | Wujiang Xu, Qitian Wu, Runzhong Wang, Mingming Ha, Qiongxu Ma, Linxun Chen, Bing Han, Junchi Yan |
| 2023 | ICLR | Energy-based Out-of-Distribution Detection for Graph Neural Networks. | Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan |
| 2023 | ICLR | DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. | Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan |
| 2023 | ICLR | Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs. | Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan |
| 2023 | KDD | GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. | Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan |
| 2023 | WWW | MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Learning. | Nianzu Yang, Kaipeng Zeng, Qitian Wu, Junchi Yan |
| 2022 | ICLR | Handling Distribution Shifts on Graphs: An Invariance Perspective. | Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf |
| 2022 | IJCAI | Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. | Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen |
| 2022 | KDD | Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation. | Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan |
| 2022 | KDD | DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness. | Qibing Ren, Yiting Chen, Yichuan Mo, Qitian Wu, Junchi Yan |
| 2021 | CIKM | Seq2Bubbles: Region-Based Embedding Learning for User Behaviors in Sequential Recommenders. | Qitian Wu, Chenxiao Yang, Shuodian Yu, Xiaofeng Gao, Guihai Chen |
| 2021 | ICML | Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach. | Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha |
| 2020 | DASFAA | SentiMem: Attentive Memory Networks for Sentiment Classification in User Review. | Xiaosong Jia, Qitian Wu, Xiaofeng Gao, Guihai Chen |
| 2019 | IJCAI | Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust. | Qitian Wu, Lei Jiang, Xiaofeng Gao, Xiaochun Yang, Guihai Chen |
| 2019 | KDD | Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. | Qitian Wu, Yirui Gao, Xiaofeng Gao, Paul Weng, Guihai Chen |
| 2019 | WWW | Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. | Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen |
| 2018 | CIKM | Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction. | Qitian Wu, Chaoqi Yang, Hengrui Zhang, Xiaofeng Gao, Paul Weng, Guihai Chen |
| 2018 | DEXA | EPOC: A Survival Perspective Early Pattern Detection Model for Outbreak Cascades. | Chaoqi Yang, Qitian Wu, Xiaofeng Gao, Guihai Chen |
| 2018 | ICDM | EPAB: Early Pattern Aware Bayesian Model for Social Content Popularity Prediction. | Qitian Wu, Chaoqi Yang, Xiaofeng Gao, Peng He, Guihai Chen |