Publications

(Underline indicates students I supervised, * indicates correpsonding author)

2024

• [NeurIPS] Yansong Ning, Hao Liu*. UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction. In Proceedings of the Thirty-eighth Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024.
• [NeurIPS] Zhao Xu, Fan Liu, Hao Liu*. Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. In Proceedings of the Thirty-eighth Annual Conference on Neural Information Processing Systems D&B track, Vancouver, Canada, 2024.
• [KDD] Weijia Zhang, Jindong Han, Zhao Xu, Hang Ni, Hao Liu* and Hui Xiong. Urban Foundation Models: A Survey. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024.
• [KDD] Wenzhao Jiang, Jindong Han, Hao Liu*, Tao Tao, Naiqiang Tan and Hui Xiong. Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024.
• [KDD] Zhuoning Guo, Duanyi Yao, Qiang Yang and Hao Liu*. HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024.
• [KDD] Weijia Zhang, Le Zhang, Jindong Han, Hao Liu*, Yanjie Fu, Jingbo Zhou, Yu Mei and Hui Xiong*. Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks. In Proceedings of the 30th SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024.
• [ICML] Weijia Zhang, Chenlong Yin, Hao Liu*, Xiaofang Zhou and Hui Xiong*. Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach. In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024.
• [VLDB] Jindong Han, Weijia Zhang, Hao Liu*, Tao Tao, Naiqiang Tan and Hui Xiong. BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks. In Proceedings of the VLDB Endowment, Guangzhou, China, 2024. Best paper nomination award
• [AAAI] Wen Shuo Chao, Zhaopeng Qiu, Likang Wu, Zhuoning Guo, Zhi Zheng, Hengshu Zhu*, Hao Liu*. A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada, 2024.
• [AAAI] Zixuan Yuan, Hao Liu, Haoyi Zhou, Denghui Zhang, Xiao Zhang, Hao Wang and Hui Xiong. Self-Paced Unified Representation Learning for Hierarchical Multi-Label Classification. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada, 2024.
• [EMNLP] Lu Dai, Hao Liu, Hui Xiong. Improve Dense Passage Retrieval with Entailment Tuning. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Miami, Florida, 2024.
• [EMNLP] Wenshuo Chao, Zhi Zheng, Hengshu Zhu*, Hao Liu*. Make Large Language Model a Better Ranker. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing Findings, Miami, Florida, 2024.
• [DASFAA] Wei Fan, Weijia Zhang, Weiqi Wang, Yangqiu Song and Hao Liu. Chain-of-Choice Hierarchical Policy Learning for Conversational Recommendation. In Proceedings of the 29th International Conference on Database Systems for Advanced Applications, Gifu, Japan, 2024.

2023

• [TKDE] Jindong Han, Hao Liu*, Hengshu Zhu, Hui Xiong. Kill Two Birds with One Stone: A Multi-View Multi-Adversarial Learning Approach for Joint Air Quality and Weather Prediction. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Yuchen Li, Haoyi Xiong, Qingzhong Wang, Linghe Kong, Hao Liu, Haifang Li, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dejing Dou, Dawei Yin. COLTR: Semi-supervised Learning to Rank with Co-training and Over-parameterization for Web Search. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Zixuan Yuan, Junming Liu, Haoyi Zhou, Denghui Zhang, Hao Liu, Nengjun Zhu and Hui Xiong. LEVER: Online Adaptive Sequence Learning Framework for High-Frequency Trading. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [Neurocomputing] Can Chen, Hao Liu*, Zeming Liu, Xue Liu, Dejing Dou. Dual-space Hierarchical Learning for Goal-guided Conversational Recommendation. Neurocomputing, Accepted.
• [KDD] Hao Liu, Wenzhao Jiang, Shui Liu, Xi Chen. Uncertainty-Aware Probabilistic Travel Time Prediction for On-Demand Ride-Hailing at DiDi. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023.
• [KDD] Fan Liu, Weijia Zhang, Hao Liu*. Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023.
• [KDD] Siqi Lai, Weijia Zhang, Hao Liu*. A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023.
• [KDD] Jindong Han, Hao Liu*, Shui Liu, Xi Chen, Naiqiang Tan, Hua Chai, Hui Xiong. iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023.
• [NuerIPS] Yansong Ning, Hao Liu*, Hao Henry Wang, Zhenyu Zeng, Hui Xiong. UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction. In Proceedings of the Thirty-seventh Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track, New Orleans, USA, 2023.
• [ICCV] Lu Dai, Liqian Ma, Shenhan Qian, Hao Liu, Hui Xiong, Ziwei Liu. Cloth2Body: Generating 3D Human Body Mesh from 2D Clothing. In Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision, Paris, France, 2023.
• [CIKM] Yuecheng Rong, Juntao Yao, Jun Liu, Yifan Fang, Wei Luo, Hao Liu,, Jie Ma, Zepeng Dan, Jinzhu Lin, Zhi Wu, Yan Zhang, Chuanming Zhang. GBTTE: Graph Attention Network Based Bus Travel Time Estimation. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, Birminghan, UK, 2023.
• [ICDM] Nengjun Zhu, Jieyun Huang, Jian Cao, Xinjiang Lu, Hao Liu, Hui Xiong. MtiRec: A Medical Test Recommender System based on the Analysis of Treatment Programs. In Proceedings of the 23rd IEEE International Conference on Data Mining, Shanghai, China, 2023.

2022

• [VLDBJ] Hao Liu, Jindong Han, Yanjie Fu, Yanyan Li, Kai Chen, Hui Xiong. Unified Route Representation Learning for Multi-Modal Transportation Recommendation with Spatiotemporal Pre-Training. The VLDB Journal, Accepted.
• [TKDE] Weijia Zhang, Hao Liu*, Tong Xu, Fan Wang, Haoran Xin, Hua Wu, Hui Xiong*. RLCharge: Imitative Multi-Agent Spatiotemporal Reinforcement Learning for Electric Vehicle Charging Station Recommendation. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Hui Xiong. Polestar++: An Intelligent Routing Engine for National-Wide Public Transportation. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Jindong Han, Hao Liu*, Haoyi Xiong, Jing Yang. Semi-Supervised Air Quality Forecasting via Self-Supervised Hierarchical Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Zeming Liu, Ding Zhou, Hao Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu, Hui Xiong. Graph-Grounded Goal Planning for Conversational Recommendation. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDD] Hao Liu, Qingyu Guo, Hengshu Zhu, Yanjie Fu, Fuzhen Zhuang, Xiaojuan Ma, Hui Xiong. Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining Perspective. ACM Transactions on Knowledge Discovery from Data, Accepted.
• [TKDD] Hao Liu, Qingyu Guo, Hengshu Zhu, Fuzhen Zhuang, Shengwen Yang, Dejing Dou, Hui Xiong. Who will Win the Data Science Competition? Insights from KDD Cup 2019 and Beyond. ACM Transactions on Knowledge Discovery from Data, Accepted.
• [TKDD] Ningjun Zhu, Jian Cao, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, Hui Xiong. Predicting a Person’s Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network. ACM Transactions on Knowledge Discovery from Data, Accepted.
• [TITS] Yuecheng Rong, Zhimian Xu, Jun Liu, Hao Liu, Jian Ding, Xuanyu Liu, Wei Luo, Chuanming Zhang, Jiaxiang Gao. Du-Bus: A Realtime Bus Waiting Time Estimation System Based On Multi-source Data. IEEE Transactions on Intelligent Transportation Systems, Accepted.
• [NeurIPS] Fan Liu, Hao Liu*, Wenzhao Jiang. Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models. In Proceedings of the Thirty-sixth Annual Conference on Neural Information Processing Systems, Virtual Conference, 2022.
• [KDD] Hao Liu, Qian Gao, Xiaochao Liao, Guangxing Chen, Hao Xiong, Silin Ren, Guobao Yang, and Zhiwei Zha. Lion: A GPU-Accelerated Online Serving System for Web-Scale Recommendation at Baidu. In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, 2022.
• [KDD] Weijia Zhang, Hao Liu*, Jindong Han, Yong Ge, and Hui Xiong*. Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing. In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, 2022.
• [KDD] Zhuoning Guo, Hao Liu*, Le Zhang, Qi Zhang, Hengshu Zhu, and Hui Xiong*. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning. In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, 2022.
• [IJCAI] Wei Fan, Kunpeng Liu, Hao Liu, Hengshu Zhu, Hui Xiong, Yanjie Fu. Feature and Instance Joint Selection: A Reinforcement Learning Perspective. In Proceedings of the 31st International Joint Conference on Artificial Intelligence, Messe Wien, Vienna, Austria, 2022.
• [AAAI] Denghui Zhang, Zixuan Yuan, Hao Liu, Xiaodong Lin and Hui Xiong. Learning to Walk with Dual Agents for Knowledge Graph Reasoning. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada, 2022.
• [ICDM] Qingyan Zhu, Yize Chen*, Hao Wang*, Zhenyu Zeng, Hao Liu*. A Knowledge-Enhanced Framework for Imitative Transportation Trajectory Generation. In Proceedings of the 22nd IEEE International Conference on Data Mining, Orlando, FL, USA, 2022.

2021

• [TKDE] Wei Fan, Kunpeng, Liu, Hao Liu, Yong Ge, Hui Xiong, Yanjie Fu. Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [KDD] Hao Liu, Qian Gao, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, Daxiang Dong, Dejing Dou, Haoyi Xiong. JiZhi: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Virtual Conference, 2021.
• [KDD] Weijia Zhang, Hao Liu*, Lijun Zha, Hengshu Zhu, Ji Liu, Dejing Dou, Hui Xiong*. MugRep: A Multi-Task Hierarchical Graph RepresentationLearning Framework for Real Estate Appraisal. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Virtual Conference, 2021.
• [KDD] Qi Zhang, Hengshu Zhu, Ying Sun, Hao Liu, Fuzhen Zhuang, Hui Xiong. Talent Demand Forecasting with Attentive Neural Sequential Model. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Virtual Conference, 2021.
• [KDD] Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao Liu, Zuohui Fu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen. Domain-oriented Language Modeling with Adaptive Hybrid Masking and Optimal Transport Alignment. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Virtual Conference, 2021.
• [WWW] Weijia Zhang, Hao Liu*, Fan Wang, Tong Xu, Haoran Xin, Dejing Dou and Hui Xiong*. A Multi-Agent Reinforcement Learning Framework for Intelligent Electric Vehicle Charging Recommendation. In Proceedings of The Web Conference 2021.
• [WWW] Zixuan Yuan, Hao Liu*, Junming Liu, Yanchi Liu, Yang Yang, Renjun Hu and Hui Xiong*. Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. In Proceedings of The Web Conference 2021.
• [VLDB] Hao Liu, Jindong Han, Yanjie Fu, Jingbo Zhou, Xinjiang Lu and Hui Xiong. Multi-Modal Transportation Recommendation with Unified Route Representation Learning. In Proceedings of the VLDB Endowment, Copenhagen, Denmark, 2021.
• [AAAI] Hao Liu, Qiyu Wu, Fuzhen Zhuang, Xinjiang Lu, Dejing Dou and Hui Xiong. Community-Aware Multi-Task Transportation Demand Prediction. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference, 2021.
• [AAAI] Jindong Han, Hao Liu*, Hengshu Zhu, Dejing Dou and Hui Xiong. Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference, 2021.
• [AAAI] Zixuan Yuan, Hao Liu*, Renjun Hu, Denghui Zhang and Hui Xiong*. Self-Supervised Prototype Representation Learning for Event-based Corporate Profiling. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference, 2021.
• [AAAI] Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou and Hui Xiong. Out-of-Town Recommendation with Travel Intention Modeling. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference, 2021.
• [NeurIPS] Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue Liu, Hao Liu, Dejing Dou. Generalized Data Weighting via Class-Level Gradient Manipulation. In Proceedings of the Thirty-fifth Annual Conference on Neural Information Processing Systems, Virtual Conference, 2021.
• [DASFAA] Ding Zhou, Hao Liu*, Tong Xu, Le Zhang, Rui Zha, Hui Xiong*, Transportation Recommendation with Fairness Consideration, In Proceedings of the 26th International Conference on Database Systems for Advanced Applications, Taipei, China, 2021.
• [SDM] Wei Fan, Kunpeng Liu, Hao Liu, Dejing Dou, Yanjie Fu. Automated Group-based Feature Selection via Interactive Reinforcement Learning. SIAM International Conference on Data Mining, Virtual Conference, 2021.
• [ICDM] Wei Fan, Kunpeng Liu, Rui Xie, Hao Liu, Hui Xiong, Yanjie Fu. Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstain Distance. In Proceedings of the 21st IEEE International Conference on Data Mining, Auckland, New Zealand, 2021. (Short paper)

2020

• [TKDE] Weijia Zhang, Hao Liu*, Yanchi Liu, Jingbo Zhou, Tong Xu and Hui Xiong*. Semi-Supervised City-Wide Parking Availability Prediction via Hierarchical Recurrent Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [TKDE] Hao Liu, Yonngxin Tong, Jindong Han, Panpan Zhang, Xinjiang Lu, and Hui Xiong. Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation. IEEE Transactions on Knowledge and Data Engineering, Accepted.
• [KDD] Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma and Hui Xiong. Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, California, 2020.
• [KDD] Shuangli Li, Jingbo Zhou, Hao Liu, Xinjiang Lu, Tong Xu and Hui Xiong. Competitive Analysis for Points of Interest. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, California, 2020.
• [SIGIR] Zixuan Yuan, Hao Liu*, Yanchi Liu, Denghui Zhang, Fei Yi, Nengjun Zhu and Hui Xiong*. Spatio-Temporal Dual Graph Attention Network for Query-POI Matching. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Xi’an, China, 2020.
• [SIGIR] Hui Luo, Jingbo Zhou, Zhifeng Bao, Shuangli Li, J. Shane Culpepper, Haochao Ying, Hao Liu and Hui Xiong. Spatial Object Recommendation with Hints: When Spatial Granularity Matters. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Xi’an, China, 2020.
• [AAAI] Weijia Zhang, Hao Liu*, Yanchi Liu, Jingbo Zhou, and Hui Xiong*. Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, New York City, USA, 2020.
• [IJCAI] Renjun Hu, Xinjiang Lu, Chuanren Liu, Yanyan Li, Hao Liu, Jingjing Gu, Shuai Ma, and Hui Xiong. Why We Go Where We Go: Profiling User Decisions on Choosing POIs. International Joint Conference on Artificial Intelligence, Yokohama, Japan, 2020.
• [ICDM] Wei Fan, Kunpeng Liu, Hao Liu, Pengyang Wang, Yong Ge and Yanjie Fu. Diversity-aware Interactive Reinforced Feature Selection. In Proceedings of the 20th IEEE International Conference on Data Mining, Sorrento, Italy, 2020. (Short paper)

2019

• [KDD] Hao Liu, Yongxin Tong, Panpan Zhang, Xinjiang Lu, Jianguo Duan, and Hui Xiong. Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Anchorage, Alaska, 2019.
• [AAAI] Hao Liu, Ting Li, Renjun Hu, Yanjie Fu, Jingjing Gu, and Hui Xiong. Joint Representation Learning for Multi-Modal Transportation Recommendation. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, USA, 2019.
• [TBD] Ting Li, Yiming Zhang, Hao Liu, Guangtao Xue, and Ling Liu. Fast Compressive Spectral Clustering for Large-Scale Sparse Graph. IEEE Transactions on Big Data, 2019.

Before 2019

• [TKDE] Hao Liu, Jiang Xiao, Haoyu Tan, Qiong Luo, Jintao Zhao, and Lionel M Ni. Efficient detection of soft concatenation mapping. IEEE Transactions on Knowledge and Data Engineering, 2018.
• [Big Data] Bing He, Dian Zhang, Siyuan Liu, Hao Liu, Dawei Han, Lionel M. Ni. Profiling driver Behavior for personalized insurance pricing and maximal profit. In 2018 IEEE International Conference on Big Data, Seattle, WA, USA, 2018.
• [CIKM] Hao Liu, Yudian Ji, Jiang Xiao, Haoyu Tan, Qiong Luo, and Lionel M Ni. TICC: Transparent inter-column compression for column-oriented database systems. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, Singapore, 2017. (Short paper)
• [APWeb-WAIM] Hao Liu, Jiang Xiao, Xianjun Guo, Haoyu Tan, Qiong Luo, and Lionel M Ni. Cuttle: Enabling cross-column compression in distributed column stores. In Asia-Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, Beijiing, China, 2017. (Short paper)
• [ICPADS] Yudian Ji, Hao Liu, Xiaoying Liu, Ye Ding, and Wuman Luo. A comparison of road-network-constrained trajectory compression methods. In 2016 IEEE 22nd International Conference on Parallel and Distributed Systems, Wuhan, China, 2016.