Denoising predictive sparse decomposition. - Long Qian; Xingjian Shi (BigComp, 2014)

Relational Stacked Denoising Autoencoder for Tag Recommendation. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (AAAI, 2015)

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. - Xingjian Shi; Zhourong Chen; Hao Wang 014; Dit-Yan Yeung; Wai-Kin Wong; Wang-chun Woo (NIPS, 2015)

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (NIPS, 2016)

Natural-Parameter Networks: A Class of Probabilistic Neural Networks. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (NIPS, 2016)

Dynamic Key-Value Memory Network for Knowledge Tracing. - Jiani Zhang 001; Xingjian Shi; Irwin King; Dit-Yan Yeung (CoRR, 2016)

Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (AAAI, 2017)

Spatiotemporal Modeling for Crowd Counting in Videos. - Feng Xiong; Xingjian Shi; Dit-Yan Yeung (ICCV, 2017)

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. - Xingjian Shi; Zhihan Gao 001; Leonard Lausen; Hao Wang 014; Dit-Yan Yeung; Wai-Kin Wong; Wang-chun Woo (NIPS, 2017)

Dynamic Key-Value Memory Networks for Knowledge Tracing. - Jiani Zhang 001; Xingjian Shi; Irwin King; Dit-Yan Yeung (WWW, 2017)

GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs. - Jiani Zhang 001; Xingjian Shi; Junyuan Xie; Hao Ma 001; Irwin King; Dit-Yan Yeung (UAI, 2018)

Machine Learning for Spatiotemporal Sequence Forecasting: A Survey. - Xingjian Shi; Dit-Yan Yeung (CoRR, 2018)

Dive into Deep Learning for Natural Language Processing. - Haibin Lin; Xingjian Shi; Leonard Lausen; Aston Zhang; He He 001; Sheng Zha; Alexander J. Smola (EMNLP/IJCNLP (2), 2019)

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. - Jiani Zhang 001; Xingjian Shi; Shenglin Zhao; Irwin King (IJCAI, 2019)

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. - Jian Guo; He He 001; Tong He 002; Leonard Lausen; Mu Li 003; Haibin Lin; Xingjian Shi; Chenguang Wang 001; Junyuan Xie; Sheng Zha; Aston Zhang; Hang Zhang 005; et al. (CoRR, 2019)

Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. - Jonas Mueller 001; Xingjian Shi; Alexander J. Smola (KDD, 2020)

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. - Jian Guo; He He 001; Tong He 002; Leonard Lausen; Mu Li 003; Haibin Lin; Xingjian Shi; Chenguang Wang 001; Junyuan Xie; Sheng Zha; Aston Zhang; Hang Zhang 005; et al. (J. Mach. Learn. Res., 2020)

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 (AAAI, 2021)

Lorien: Efficient Deep Learning Workloads Delivery. - Cody Hao Yu; Xingjian Shi; Haichen Shen; Zhi Chen 030; Mu Li 003; Yida Wang 003 (SoCC, 2021)

Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. - Haoyu He; Xingjian Shi; Jonas Mueller 001; Sheng Zha; Mu Li 003; George Karypis (SustaiNLP@EMNLP, 2021)

Benchmarking Multimodal AutoML for Tabular Data with Text Fields. - Xingjian Shi; Jonas Mueller 001; Nick Erickson; Mu Li 003; Alexander J. Smola (NeurIPS Datasets and Benchmarks, 2021)

Removing Batch Normalization Boosts Adversarial Training. - Haotao Wang; Aston Zhang; Shuai Zheng 004; Xingjian Shi; Mu Li 003; Zhangyang Wang (ICML, 2022)

Multimodal AutoML for Image, Text and Tabular Data. - Nick Erickson; Xingjian Shi; James Sharpnack; Alexander J. Smola (KDD, 2022)

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. - Zhihan Gao 001; Xingjian Shi; Hao Wang 014; Yi Zhu 001; Yuyang Wang 001; Mu Li 003; Dit-Yan Yeung (NeurIPS, 2022)

Fix Bugs with Transformer through a Neural-Symbolic Edit Grammar. - Yaojie Hu; Xingjian Shi; Qiang Zhou; Lee Pike (CoRR, 2022)

Visual Prompt Tuning for Test-time Domain Adaptation. - Yunhe Gao; Xingjian Shi; Yi Zhu 001; Hao Wang 014; Zhiqiang Tang 001; Xiong Zhou; Mu Li 003; Dimitris N. Metaxas (CoRR, 2022)

Are Multimodal Models Robust to Image and Text Perturbations? - Jielin Qiu; Yi Zhu 001; Xingjian Shi; Florian Wenzel; Zhiqiang Tang 001; Ding Zhao; Bo Li 026; Mu Li 003 (CoRR, 2022)

First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting. - Xiyuan Zhang; Xiaoyong Jin; Karthick Gopalswamy; Gaurav Gupta; Youngsuk Park; Xingjian Shi; Hao Wang 014; Danielle C. Maddix; Yuyang Wang 001 (CoRR, 2022)

SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning. - M. Saiful Bari; Aston Zhang; Shuai Zheng 004; Xingjian Shi; Yi Zhu 001; Shafiq Joty; Mu Li 003 (CoRR, 2022)

Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. - Yuxin Ren; Zihan Zhong; Xingjian Shi; Yi Zhu 001; Chun Yuan; Mu Li 003 (ACL (1), 2023)

Automated Few-Shot Classification with Instruction-Finetuned Language Models. - Rami Aly; Xingjian Shi; Kaixiang Lin; Aston Zhang; Andrew Gordon Wilson (EMNLP (Findings), 2023)

Towards Geospatial Foundation Models via Continual Pretraining. - Matías Mendieta; Boran Han; Xingjian Shi; Yi Zhu 001; Chen Chen 001 (ICCV, 2023)

Parameter-Efficient Fine-Tuning Design Spaces. - Jiaao Chen; Aston Zhang; Xingjian Shi; Mu Li 003; Alex Smola; Diyi Yang (ICLR, 2023)

Learning Multimodal Data Augmentation in Feature Space. - Zichang Liu; Zhiqiang Tang 001; Xingjian Shi; Aston Zhang; Mu Li 003; Anshumali Shrivastava; Andrew Gordon Wilson (ICLR, 2023)

XTab: Cross-table Pretraining for Tabular Transformers. - Bingzhao Zhu; Xingjian Shi; Nick Erickson; Mu Li 003; George Karypis; Mahsa Shoaran (ICML, 2023)

PreDiff: Precipitation Nowcasting with Latent Diffusion Models. - Zhihan Gao 001; Xingjian Shi; Boran Han; Hao Wang 014; Xiaoyong Jin; Danielle C. Maddix; Yi Zhu 001; Mu Li 003; Yuyang Wang 001 (NeurIPS, 2023)

A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data. - Wenting Ye; Hongfei Yang; Shuai Zhao; Haoyang Fang; Xingjian Shi; Naveen Neppalli (SIGIR, 2023)

GFM: Building Geospatial Foundation Models via Continual Pretraining. - Matías Mendieta; Boran Han; Xingjian Shi; Yi Zhu 001; Chen Chen 001; Mu Li 003 (CoRR, 2023)

LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation. - Jiaxin Cheng; Xiao Liang; Xingjian Shi; Tong He 002; Tianjun Xiao; Mu Li 003 (CoRR, 2023)

Bridging Remote Sensors with Multisensor Geospatial Foundation Models. - Boran Han; Shuai Zhang 007; Xingjian Shi; Markus Reichstein (CVPR, 2024)

BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics. - Hao Wu; Xingjian Shi; Ziyue Huang; Penghao Zhao; Wei Xiong; Jinbao Xue; Yangyu Tao; Xiaomeng Huang; Weiyan Wang (CoRR, 2024)

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 (HCI (8), 2025)

Genetic Programming-Based Hyper-Heuristic Algorithm for Dynamic Task Scheduling in Astronomical Observation Satellite. - Ziruo Fang; Ningbiao Tang; Zhencai Zhu; Xingjian Shi; Wen Chen (ICIC (13), 2025)

L3Ms - Lagrange Large Language Models. - Guneet S. Dhillon; Xingjian Shi; Yee Whye Teh; Alex Smola (ICLR, 2025)

RPGBENCH: Evaluating Large Language Models as Role-Playing Game Engines. - Pengfei Yu; Dongming Shen; Silin Meng; Jaewon Lee; Weisu Yin; Andrea Yaoyun Cui; Zhenlin Xu; Yi Zhu 001; Xingjian Shi; Mu Li 003; Alex Smola (CoRR, 2025)

BeamVQ: Beam Search with Vector Quantization to Mitigate Data Scarcity in Physical Spatiotemporal Forecasting. - Weiyan Wang; Xingjian Shi; Ruiqi Shu; Yuan Gao; Rui Ray Chen; Kun Wang 042; Fan Xu 009; Jinbao Xue; Shuaipeng Li; Yangyu Tao; Di Wang; Hao Wu 094; et al. (CoRR, 2025)

Advanced long-term earth system forecasting by learning the small-scale nature. - Hao Wu; Yuan Gao; Ruiqi Shu; Kun Wang 056; Ruijian Gou; Chuhan Wu; Xinliang Liu; Juncai He; Shuhao Cao; Junfeng Fang; Xingjian Shi; Feng Tao; et al. (CoRR, 2025)

EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judge. - Ruskin Raj Manku; Yuzhi Tang; Xingjian Shi; Mu Li 003; Alex Smola (CoRR, 2025)