Xingjian Shi

According to our database, Xingjian Shi authored at least 42 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

L3Ms - Lagrange Large Language Models.

Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh, Alex Smola

CoRR, 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

Bridging Remote Sensors with Multisensor Geospatial Foundation Models.

Boran Han, Shuai Zhang, Xingjian Shi, Markus Reichstein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation.

Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li

CoRR, 2023

GFM: Building Geospatial Foundation Models via Continual Pretraining.

Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, Mu Li

CoRR, 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

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

PreDiff: Precipitation Nowcasting with Latent Diffusion Models.

Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

XTab: Cross-table Pretraining for Tabular Transformers.

Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran

Proceedings of the International Conference on Machine Learning, 2023

Learning Multimodal Data Augmentation in Feature Space.

Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Parameter-Efficient Fine-Tuning Design Spaces.

Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Geospatial Foundation Models via Continual Pretraining.

Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Automated Few-Shot Classification with Instruction-Finetuned Language Models.

Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation.

Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning.

M. Saiful Bari, Aston Zhang, Shuai Zheng, Xingjian Shi, Yi Zhu, Shafiq Joty, Mu Li

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, Danielle C. Maddix, Yuyang Wang

CoRR, 2022

Are Multimodal Models Robust to Image and Text Perturbations?

Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

CoRR, 2022

Visual Prompt Tuning for Test-time Domain Adaptation.

Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas

CoRR, 2022

Fix Bugs with Transformer through a Neural-Symbolic Edit Grammar.

Yaojie Hu, Xingjian Shi, Qiang Zhou, Lee Pike

CoRR, 2022

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.

Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multimodal AutoML for Image, Text and Tabular Data.

Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Removing Batch Normalization Boosts Adversarial Training.

Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang

Proceedings of the International Conference on Machine Learning, 2022

2021

Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing.

Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis

Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, 2021

Lorien: Efficient Deep Learning Workloads Delivery.

Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang

Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.

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

J. Mach. Learn. Res., 2020

Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data.

Jonas Mueller, Xingjian Shi, Alexander J. Smola

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.

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

CoRR, 2019

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems.

Jiani Zhang, Xingjian Shi, Shenglin Zhao, Irwin King

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Dive into Deep Learning for Natural Language Processing.

Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Machine Learning for Spatiotemporal Sequence Forecasting: A Survey.

Xingjian Shi, Dit-Yan Yeung

CoRR, 2018

GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs.

Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2017

Dynamic Key-Value Memory Networks for Knowledge Tracing.

Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung

Proceedings of the 26th International Conference on World Wide Web, 2017

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model.

Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Spatiotemporal Modeling for Crowd Counting in Videos.

Feng Xiong, Xingjian Shi, Dit-Yan Yeung

Proceedings of the IEEE International Conference on Computer Vision, 2017

Relational Deep Learning: A Deep Latent Variable Model for Link Prediction.

Hao Wang, Xingjian Shi, Dit-Yan Yeung

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Dynamic Key-Value Memory Network for Knowledge Tracing.

Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung

CoRR, 2016

Natural-Parameter Networks: A Class of Probabilistic Neural Networks.

Hao Wang, Xingjian Shi, Dit-Yan Yeung

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks.

Hao Wang, Xingjian Shi, Dit-Yan Yeung

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.

Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Relational Stacked Denoising Autoencoder for Tag Recommendation.

Hao Wang, Xingjian Shi, Dit-Yan Yeung

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Denoising predictive sparse decomposition.

Long Qian, Xingjian Shi

Proceedings of the International Conference on Big Data and Smart Computing, BIGCOMP 2014, 2014