Xingjian Shi

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 58

Top Topics

Natural Language Processing

Probabilistic Neural Networks

Top Venues

Publications

Hao Wu, Xingjian Shi, Ziyue Huang, Penghao Zhao, Wei Xiong, Jinbao Xue, Yangyu Tao, Xiaomeng Huang, Weiyan Wang
BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics. CoRR (2024)
Boran Han, Shuai Zhang, Xingjian Shi, Markus Reichstein
Bridging Remote Sensors with Multisensor Geospatial Foundation Models. CoRR (2024)
Wenting Ye, Hongfei Yang, Shuai Zhao, Haoyang Fang, Xingjian Shi, Naveen Neppalli
A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data. SIGIR (2023)
Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation. CoRR (2023)
Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran
XTab: Cross-table Pretraining for Tabular Transformers. ICML (2023)
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. CoRR (2023)
Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, Mu Li
GFM: Building Geospatial Foundation Models via Continual Pretraining. CoRR (2023)
Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson
Automated Few-Shot Classification with Instruction-Finetuned Language Models. EMNLP (Findings) (2023)
Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. ACL (1) (2023)
Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson
Automated Few-shot Classification with Instruction-Finetuned Language Models. CoRR (2023)
Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang
Parameter-Efficient Fine-Tuning Design Spaces. CoRR (2023)
Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. CoRR (2023)
Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran
XTab: Cross-table Pretraining for Tabular Transformers. CoRR (2023)
Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen
Towards Geospatial Foundation Models via Continual Pretraining. ICCV (2023)
Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
Learning Multimodal Data Augmentation in Feature Space. ICLR (2023)
Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang
Parameter-Efficient Fine-Tuning Design Spaces. ICLR (2023)
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. NeurIPS (2023)
Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang
Removing Batch Normalization Boosts Adversarial Training. ICML (2022)
Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
Are Multimodal Models Robust to Image and Text Perturbations? CoRR (2022)
Yaojie Hu, Xingjian Shi, Qiang Zhou, Lee Pike
Fix Bugs with Transformer through a Neural-Symbolic Edit Grammar. CoRR (2022)
Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Yuyang Wang
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting. CoRR (2022)
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS (2022)
Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola
Multimodal AutoML for Image, Text and Tabular Data. KDD (2022)
M. Saiful Bari, Aston Zhang, Shuai Zheng, Xingjian Shi, Yi Zhu, Shafiq Joty, Mu Li
SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning. CoRR (2022)
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. CoRR (2022)
Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
Learning Multimodal Data Augmentation in Feature Space. CoRR (2022)
Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang
Removing Batch Normalization Boosts Adversarial Training. CoRR (2022)
Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas
Visual Prompt Tuning for Test-time Domain Adaptation. CoRR (2022)
Wenting Ye, Hongfei Yang, Shuai Zhao, Haoyang Fang, Xingjian Shi, Naveen Neppalli
A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data. CoRR (2022)
Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
Benchmarking Multimodal AutoML for Tabular Data with Text Fields. CoRR (2021)
Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR (2021)
Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
Benchmarking Multimodal AutoML for Tabular Data with Text Fields. NeurIPS Datasets and Benchmarks (2021)
Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP (2021)
Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola
Symbolic Music Generation with Transformer-GANs. AAAI (2021)
Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang
Lorien: Efficient Deep Learning Workloads Delivery. SoCC (2021)
Jonas Mueller, Xingjian Shi, Alexander J. Smola
Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. KDD (2020)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 21 (2020)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR (2019)
Jiani Zhang, Xingjian Shi, Shenglin Zhao, Irwin King
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. IJCAI (2019)
Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) (2019)
Jiani Zhang, Xingjian Shi, Shenglin Zhao, Irwin King
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems. CoRR (2019)
Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung
GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs. UAI (2018)
Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung
GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs. CoRR (2018)
Xingjian Shi, Dit-Yan Yeung
Machine Learning for Spatiotemporal Sequence Forecasting: A Survey. CoRR (2018)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. AAAI (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. NIPS (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. CoRR (2017)
Feng Xiong, Xingjian Shi, Dit-Yan Yeung
Spatiotemporal Modeling for Crowd Counting in Videos. CoRR (2017)
Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung
Dynamic Key-Value Memory Networks for Knowledge Tracing. WWW (2017)
Feng Xiong, Xingjian Shi, Dit-Yan Yeung
Spatiotemporal Modeling for Crowd Counting in Videos. ICCV (2017)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. CoRR (2016)
Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung
Dynamic Key-Value Memory Network for Knowledge Tracing. CoRR (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Natural-Parameter Networks: A Class of Probabilistic Neural Networks. CoRR (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Natural-Parameter Networks: A Class of Probabilistic Neural Networks. NIPS (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. NIPS (2016)
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. NIPS (2015)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Relational Stacked Denoising Autoencoder for Tag Recommendation. AAAI (2015)
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. CoRR (2015)
Long Qian, Xingjian Shi
Denoising predictive sparse decomposition. BigComp (2014)