| 2025 | HCI | Effects of Dynamic Visual Coding of Point Symbols in Map-Based Information Visualization Design: An Eye-Tracking Study. | Weijia Ge, Jing Zhang, Shangsong Jiang, Xingjian Shi, Yanxu Zhou |
| 2025 | ICLR | L3Ms - Lagrange Large Language Models. | Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh, Alex Smola |
| 2024 | CVPR | Bridging Remote Sensors with Multisensor Geospatial Foundation Models. | Boran Han, Shuai Zhang, Xingjian Shi, Markus Reichstein |
| 2023 | ACL | Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. | Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li |
| 2023 | EMNLP | Automated Few-Shot Classification with Instruction-Finetuned Language Models. | Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson |
| 2023 | ICCV | Towards Geospatial Foundation Models via Continual Pretraining. | Matas Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen |
| 2023 | ICLR | Parameter-Efficient Fine-Tuning Design Spaces. | Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang |
| 2023 | ICLR | Learning Multimodal Data Augmentation in Feature Space. | Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson |
| 2023 | ICML | XTab: Cross-table Pretraining for Tabular Transformers. | Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran |
| 2023 | SIGIR | A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data. | Wenting Ye, Hongfei Yang, Shuai Zhao, Haoyang Fang, Xingjian Shi, Naveen Neppalli |
| 2022 | ICML | Removing Batch Normalization Boosts Adversarial Training. | Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang |
| 2022 | KDD | Multimodal AutoML for Image, Text and Tabular Data. | Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola |
| 2021 | AAAI | Symbolic Music Generation with Transformer-GANs. | Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola |
| 2021 | CLOUD | Lorien: Efficient Deep Learning Workloads Delivery. | Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang |
| 2021 | EMNLP | Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. | Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis |
| 2020 | KDD | Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. | Jonas Mueller, Xingjian Shi, Alexander J. Smola |
| 2019 | EMNLP | Dive into Deep Learning for Natural Language Processing. | Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola |
| 2019 | IJCAI | STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. | Jiani Zhang, Xingjian Shi, Shenglin Zhao, Irwin King |
| 2018 | UAI | GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs. | Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung |
| 2017 | AAAI | Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. | Hao Wang, Xingjian Shi, Dit-Yan Yeung |
| 2017 | ICCV | Spatiotemporal Modeling for Crowd Counting in Videos. | Feng Xiong, Xingjian Shi, Dit-Yan Yeung |
| 2017 | WWW | Dynamic Key-Value Memory Networks for Knowledge Tracing. | Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung |
| 2015 | AAAI | Relational Stacked Denoising Autoencoder for Tag Recommendation. | Hao Wang, Xingjian Shi, Dit-Yan Yeung |