Publications

Listed by categories in reversed chronological order, where + indicates equal contribution and * denotes corresponding author.

Dr. Yuxuan Liang has published some papers in refereed journals and conferences, including DM venues (e.g., KDD*12, WWW*7, ICDE*3, TKDE*6, TMC*1), AI venues (e.g., TPAMI*2, AI Journal*2, NeurIPS*5, ICML*3, IJCAI*7, AAAI*5, ICLR*4), and CV venues (e.g., ECCV*1, MM*3). Here are some representative papers:

2024

  1. ICML’24
    [New] Position Paper: What Can Large Language Models Tell Us about Time Series Analysis
    Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang*, Bin Yang, Jindong Wang, Shirui Pan, and Qingsong Wen*
    In International Conference on Machine Learning, 2024
  2. ICML’24
    [New] Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
    Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, and Yang You
    In International Conference on Machine Learning, 2024
  3. ICML’24
    [New] Two heads are better than one: Boosting graph sparse training via semantic and topological awareness
    Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, and Tianlong Chen
    In International Conference on Machine Learning, 2024
  4. IJCAI’24
    [New] Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning.
    Kang Luo, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, and Yuxuan Liang*
    In International Joint Conference on Artificial Intelligence, 2024
  5. [New] Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
    Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, and Shirui Pan
    IEEE Transactions on Pattern Analysis and Machine Intelligence 2024
  6. [New] Semantic-fused multi-granularity cross-city traffic prediction
    Kehua Chen, Yuxuan Liang, Jindong Han, Siyuan Feng, Meixin Zhu, and Hai Yang
    Transportation Research Part C: Emerging Technologies 2024
  7. [New] Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts
    Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang*, Yuankai Wu, Roger Zimmermann, and Yang Wang*
    IEEE Transactions on Knowledge and Data Engineering 2024
  8. WWW’24
    [New] UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web
    Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang*
    In The Web Conference, 2024
  9. WWW’24
    [New] UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting
    Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang*, Bryan Hooi, and Roger Zimmermann
    In The Web Conference, 2024
  10. WWW’24
    [New] COLA: Cross-city Mobility Transformer for Human Trajectory Simulation
    Yu Wang, Tongya Zheng, Yuxuan Liang, Shunyu Liu, and Mingli Song
    In The Web Conference, 2024
  11. ICLR’24
    NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling
    Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, Yu Zheng, Yuxuan Liang*, and Yang Wang*
    In The International Conference on Learning Representations, 2024
  12. ICLR’24
    Graph Lottery Ticket Automated
    Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng*, and Yuxuan Liang*
    In The International Conference on Learning Representations, 2024
  13. ICLR’24
    Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
    Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, and Qingsong Wen
    In The International Conference on Learning Representations, 2024
  14. AAAI’24
    Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
    Hao Wu, Shilong Wang, Yuxuan Liang, Zhengyang Zhou, Wei Huang, Wei Xiong, and Kun Wang
    In Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
  15. AAAI’24
    MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
    Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, and Yuankai Wu*
    In Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
  16. AAAI’24
    SENCR: A Span Enhanced Two-stage Network with Counterfactual Rethinking for Chinese NER
    Hang Zheng, Qingsong Li, Shen Chen, Yuxuan Liang, and Li Liu*
    In Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
  17. ICASSP’24
    Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data
    Guorui Liao, Jiawei Liu, Yuxuan Liang, Shu Wang, and Li Liu*
    In IEEE ICASSP, 2024
  18. ICDE’24
    Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Anomaly Detection
    Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, and Shuiguang Deng
    In The 40th IEEE International Conference on Data Engineering, 2024
  19. ICDE’24
    Urban Sensing for Multi-Destination Workers via Deep Reinforcement Learning
    Shuliang Wang, Song Tang, Sijie Ruan*, Cheng Long, Yuxuan Liang, Qi Li, Ziqiang Yuan, Jie Bao, and Yu Zheng
    In The 40th IEEE International Conference on Data Engineering, 2024
  20. WSDM’24
    CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting
    Chengxin Wang, Yuxuan Liang, and Gary Tan
    In The 17th ACM International Conference on Web Search and Data Mining, 2024

2023

  1. End-to-end Delay Modeling via Leveraging Competitive Interaction among Network Flows
    Weiping Zheng, Minli Hong, Ruihao Ye, Xiaomao Fan, Yuxuan Liang, Gansen Zhao, and Roger Zimmermann
    IEEE Transactions on Network and Service Management 2023
  2. Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets
    Kun Wang, Yuxuan Liang*, Xinglin Li, Guohao Li, Bernard Ghanem, Roger Zimmermann, Zhengyang Zhou, huahui Yi, Yudong Zhang, and Yang Wang*
    IEEE Transactions on Pattern Analysis and Machine Intelligence 2023
  3. Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
    Guangyin Jin, Yuxuan Liang*, Yuchen Fang, Jincai Huang, Junbo Zhang, and Yu Zheng
    IEEE Transactions on Knowledge and Data Engineering 2023
  4. NeurIPS’23
    Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
    Yutong Xia, Yuxuan Liang*, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, and Roger Zimmermann
    In Advances in neural information processing systems, 2023
  5. EMNLP’23
    Primacy Effect of ChatGPT
    Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, and Bryan Hooi
    In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
  6. NeurIPS’23
    LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (Datasets and Benchmarks Track Paper)
    Xu Liu, Yutong Xia, Yuxuan Liang*, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, and Roger Zimmermann
    In Advances in neural information processing systems, 2023
  7. SIGSPATIAL’23
    DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
    Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang*
    In Proceedings of the 31st International Conference on Advances in Geographic Information Systems, 2023
  8. MM’23
    PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search
    Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Xianjing Han, Hannes Kruppa, See-Kiong Ng, and Roger Zimmermann
    In ACM Multimedia, 2023
  9. Predicting collective human mobility via countering spatiotemporal heterogeneity
    Zhengyang Zhou, Kuo Yang, Yuxuan Liang, Binwu Wang, Hongyang Chen, and Yang Wang
    IEEE Transactions on Mobile Computing 2023
  10. Decoupling Long-and Short-Term Patterns in Spatiotemporal Inference
    Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Yifang Yin, Ying Zhang, and Roger Zimmermann
    IEEE Transactions on Neural Networks and Learning Systems 2023
  11. KDD’23
    Graph Neural Processes for Spatio-Temporal Extrapolation
    Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Hongyang Chen, Yu Zheng, and Roger Zimmermann
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  12. KDD’23
    Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning
    Zhengyang Zhou, Qihe Huang, Kuo Yang, Kun Wang, Xu Wang, Yudong Zhang, Yuxuan Liang, and Yang Wang
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  13. AutoSTG+: An Automatic Framework to Discover The Optimal Network for Spatio-temporal Graph Prediction
    Songyu Ke, Zheyi Pan, Tianfu He, Yuxuan Liang, Junbo Zhang, and Yu Zheng
    Artificial Intelligence 2023
  14. ICDE’23
    Contrastive Trajectory Similarity Learning with Dual-Feature Attention
    Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, and Egemen Tanin
    In The 39th IEEE International Conference on Data Engineering, 2023
  15. ICLR’23
    Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
    Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, and Yang Wang*
    In The International Conference on Learning Representations, 2023
  16. AAAI’23
    AirFormer: Predicting Nationwide Air Quality in China with Transformers
    Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, and Roger Zimmermann
    In Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

  1. Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, Zheyi Pan, Yifang Yin, Hongyang Chen, Junbo Zhang, Yu Zheng, David S Rosenblum, and Roger Zimmermann
    IEEE Transactions on Knowledge and Data Engineering 2022
  2. SIGSPATIAL’22
    When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?
    Xu Liu+, Yuxuan Liang+, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann
    In Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022
  3. ECCV’22
    Dualformer: Local-global stratified transformer for efficient video recognition
    Yuxuan Liang, Pan Zhou, Roger Zimmermann, and Shuicheng Yan
    In European Conference on Computer Vision, 2022
  4. CIKM’22
    TrajFormer: Efficient Trajectory Classification with Transformers
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, Xu Liu, Hongyang Chen, Junbo Zhang, Yu Zheng, and Roger Zimmermann
    In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
  5. SIGSPATIAL’22
    Periodic Residual Learning for Crowd Flow Forecasting
    Chengxin Wang, Yuxuan Liang, and Gary Tan
    In Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022
  6. KDD’22
    Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
    Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, and Chenliang Li
    In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022
  7. MM’22
    Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery
    Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Andrei Georgescu, An Tran, Hannes Kruppa, See-Kiong Ng, and Roger Zimmermann
    In Proceedings of the 30th ACM International Conference on Multimedia, 2022
  8. Content-Attribute Disentanglement for Generalized Zero-Shot Learning
    Yoojin An, Sangyeon Kim, Yuxuan Liang, Roger Zimmermann, Dongho Kim, and Jihie Kim
    IEEE Access 2022
  9. IJCNN’22
    Time-Aware Neighbor Sampling on Temporal Graphs
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, and Bryan Hooi
    In 2022 International Joint Conference on Neural Networks (IJCNN), 2022
  10. NAACL’22
    Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis
    Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, and Bryan Hooi
    In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021

  1. IJCAI’21
    Modeling Trajectories with Neural Ordinary Differential Equations.
    Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, and Roger Zimmermann
    In International Joint Conference on Artificial Intelligence, 2021
  2. WWW’21
    Fine-grained Urban Flow Prediction
    Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, and Roger Zimmermann
    In Proceedings of the Web Conference, 2021
  3. WWW’21
    AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph
    Zheyi Pan, Songyu Ke, Xiaodu Yang, Yuxuan Liang, Yong Yu, Junbo Zhang, and Yu Zheng
    In Proceedings of the Web Conference, 2021
  4. WWW’21
    Mixup for Node and Graph Classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, and Bryan Hooi
    In Proceedings of the Web Conference, 2021
  5. WWW’21
    Curgraph: Curriculum learning for graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, and Bryan Hooi
    In Proceedings of the Web Conference, 2021
  6. NeurIPS’21
    Directed Graph Contrastive Learning
    Zekun Tong, Yuxuan Liang, Henghui Ding, Yongxing Dai, Xinke Li, and Changhu Wang
    Advances in Neural Information Processing Systems 2021
  7. NeurIPS’21
    Adaptive Data Augmentation on Temporal Graphs
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, and Bryan Hooi
    Advances in Neural Information Processing Systems 2021
  8. MM’21
    Learning Multi-context Aware Location Representations from Large-scale Geotagged Images
    Yifang Yin, Ying Zhang, Zhenguang Liu, Yuxuan Liang, Sheng Wang, Rajiv Ratn Shah, and Roger Zimmermann
    In Proceedings of the 29th ACM International Conference on Multimedia, 2021
  9. Visual Cascade Analytics of Large-Scale Spatiotemporal Data
    Zikun Deng, Di Weng, Yuxuan Liang, Jie Bao, Yu Zheng, Tobias Schreck, Mingliang Xu, and Yingcai Wu
    IEEE Transactions on Visualization and Computer Graphics 2021
  10. Structure-Aware Label Smoothing for Graph Neural Networks
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, and Bryan Hooi
    arXiv preprint arXiv:2112.00499 2021

2020

  1. KDD’20
    Nodeaug: Semi-Supervised Node Classification with Data Augmentation
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, and Bryan Hooi
    In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020
  2. NeurIPS’20
    Digraph Inception Convolutional Networks
    Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, and Andrew Lim
    Advances in neural information processing systems 2020
  3. ECML-PKDD’20
    Revisiting convolutional neural networks for citywide crowd flow analytics
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, and David S Rosenblum
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020
  4. KDD’20
    Autost: Efficient Neural Architecture Search for Spatio-Temporal Prediction
    Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, and Yu Zheng
    In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020
  5. Fine-grained Urban Flow Inference
    Kun Ouyang, Yuxuan Liang, Ye Liu, Zekun Tong, Sijie Ruan, David Rosenblum, and Yu Zheng
    IEEE transactions on knowledge and data engineering 2020
  6. Predicting Citywide Crowd Flows in Irregular Regions using Multi-View Graph Convolutional Networks
    Junkai Sun, Junbo Zhang, Qiaofei Li, Xiuwen Yi, Yuxuan Liang, and Yu Zheng
    IEEE Transactions on Knowledge and Data Engineering 2020
  7. Spatio-Temporal Meta Learning for Urban Traffic Prediction
    Zheyi Pan, Wentao Zhang, Yuxuan Liang, Weinan Zhang, Yong Yu, Junbo Zhang, and Yu Zheng
    IEEE Transactions on Knowledge and Data Engineering 2020
  8. Predicting Urban Water Quality with Ubiquitous Data - a Data-Driven Approach
    Ye Liu, Yuxuan Liang, Kun Ouyang, Shuming Liu, David Rosenblum, and Yu Zheng
    IEEE Transactions on Big Data 2020
  9. UBICOMP’20
    Dynamic Public Resource Allocation based on Human Mobility Prediction
    Sijie Ruan, Jie Bao, Yuxuan Liang, Ruiyuan Li, Tianfu He, Chuishi Meng, Yanhua Li, Yingcai Wu, and Yu Zheng
    Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 2020
  10. AAAI’20
    Learning to Generate Maps from Trajectories
    Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, and Yu Zheng
    In Proceedings of the AAAI conference on artificial intelligence, 2020
  11. ECML-PKDD’20
    Progressive Supervision for Node Classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, and Bryan Hooi
    In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020
  12. Federated Forest
    Yang Liu, Yingting Liu, Zhijie Liu, Yuxuan Liang, Chuishi Meng, Junbo Zhang, and Yu Zheng
    IEEE Transactions on Big Data 2020
  13. IJCNN’20
    Unsupervised Learning of Disentangled Location Embeddings
    Kun Ouyang, Yuxuan Liang, Ye Liu, David S Rosenblum, and Wenzhuo Yang
    In 2020 International Joint Conference on Neural Networks (IJCNN), 2020
  14. Graphcrop: Subgraph cropping for graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, and Bryan Hooi
    arXiv preprint arXiv:2009.10564 2020

2019

  1. KDD’19
    Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
    Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, and Junbo Zhang
    In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
  2. KDD’19
    Urbanfm: Inferring Fine-Grained Urban Flows
    Yuxuan Liang+, Kun Ouyang+, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S Rosenblum, and Yu Zheng
    In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining, 2019
  3. IJCAI’19
    Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking.
    Nirandika Wanigasekara, Yuxuan Liang, Siong Thye Goh, Ye Liu, Joseph Jay Williams, and David S Rosenblum
    In International Joint Conference on Artificial Intelligence, 2019

2018

  1. IJCAI’18
    GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction.
    Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, and Yu Zheng
    In International Joint Conference on Artificial Intelligence, 2018

2017

  1. SIGSPATIAL’17
    Inferring Traffic Cascading Patterns
    Yuxuan Liang, Zhongyuan Jiang, and Yu Zheng
    In Proceedings of the 25th acm sigspatial international conference on advances in geographic information systems, 2017

2016

  1. IJCAI’16
    Urban Water Quality Prediction based on Multi-Task Multi-View Learning
    Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, and David S Rosenblum
    In Proceedings of the 25th international joint conference on artificial intelligence, 2016