Selected Publications:
Publication by date is available here and Publication by topic is available here.
- Haoye Chai, Shiyuan Zhang, Xiaoqian Qi, Baohua Qiu, Yong Li. UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization, in Knowledge Discovery and Data Mining 2025.
(KDD 2025)
Code
PDF
- Haoye Chai, Tong Li, Fenyu Jiang, Shiyuan Zhang, Yong Li. Knowledge Guided Conditional Diffusion Model for Controllable Mobile Traffic Generation, in International World Wide Web Conference 2024 (short paper). (WWW 2024)
- Nian Li, Chen Gao, Mingyu Li, Yong Li, Qingmin Liao. EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities, in ACL 2024.
(ACL 2024)
Code
- Xin Zhang, Yu Liu, Yuming Lin, Qingmin Liao, Yong Li. UV-SAM: Adapting Segment Anything Model for Urban Village Identification, in The 38th Annual AAAI Conference on Artificial Intelligence, 2024. (AAAI 2024)
- Hongyi Chen, Jingtao Ding, Yong Li, Yue Wang, Xiao-Ping Zhang. Social Physics Informed Diffusion Model for Crowd Simulation, in The 38th Annual AAAI Conference on Artificial Intelligence, 2024. (AAAI 2024)
- Jiahui Gong, Qiaohong Yu, Tong Li, Haoqiang Liu, Jun Zhang, Hangyu Fan, Depeng Jin, Yong Li. Scalable Digital Twin System for Mobile Networks with Generative AI, in MobiSys 2023. (MobiSys 2023)
- Tong Li, Li Yu, Yibo Ma, Tong Duan, Wenzheng Huang, Yan Zhou, Depeng Jin, Yong Li, Tao Jiang. Carbon Emissions of 5G Mobile Networks in China, in Nature Sustainability,6,1620-1631.
(Nat. Sustain.)
Code
PDF
- Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin and Yong Li. Spatio-temporal Diffsuion Point Processes, in KDD 2023.
(KDD 2023)
Code
PDF
- Shuodi Hui, Huandong Wang, Tong Li, Xinghao Yang, Xing Wang, Junlan Feng, Lin Zhu, Chao Deng, Hui Pan, Depeng Jin, Yong Li. Large-scale Urban Cellular Traffic Generation via Knowledge-Enhanced GANs with Multi-Periodic Patterns, in KDD 2023.
(KDD 2023)
Code
PDF
- Shiyuan Zhang, Tong Li，Shuodi Hui, Guangyu Li, Yanping Liang, Zhe Lyu, Li Yu, Depeng Jin, Yong Li. Deep Transfer Learning for City-scale Cellular Traffic Generation through Urban Knowledge Graph, in KDD 2023.
(KDD 2023)
Code
PDF
- Ruikun Li, Huandong Wang, Yong Li. Learning Slow and Fast System Dynamics via Automatic Separation of Time Scales, in KDD 2023.
(KDD 2023)
Code
PDF
- Qingyue Long, Huandong Wang, Tong Li, Lisi Huang, Kun Wang, Qiong Wu, Guangyu Li, Yanping Liang, Li Yu and Yong Li. Practical Synthetic Human Trajectories Generation Based on Variational Point Processes, in KDD 2023.
(KDD 2023)
Code
PDF
- Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, and Yong Li. Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network, in KDD 2023.
(KDD 2023)
Code
PDF
- Hongzhi Shi, Quanming Yao, and Yong Li. Learning to Simulate Crowd Trajectories with Graph Networks, in The WebConf 2023. (WWW2023)
- Hongzhi Shi, Jingtao Ding, Yufan Cao, Quanming Yao, Li Liu, Yong Li. Learning Symbolic Models for Graph-structured Physical Mechanism, in ICLR 2023. (ICLR 2023)
- Guozhen Zhang, Tian Ye, Jian Yuan, Depeng Jin, Yong Li. A Multi-scale Co-evolving Model for Dynamic Link Prediction in Evolving Networks, in The WebConf 2023.
(WWW2023)
PDF
- Yuan Yuan, Huandong Wang, Jingtao Ding, Depeng Jin, and Yong Li. Learning to Simulate Daily Activities via Modeling Dynamic Human Needs, in The WebConf2023.
(WWW2023)
PDF
- Yuan Yuan, Jingtao Ding, Huandong Wang, Depeng Jin, and Yong li. Activity Trajectory Generation via Modeling Spatiotemporal Dynamics, in KDD 2022（health day）.
(KDD)
Code
PDF
- Guozhen Zhang, Zihan Yu, Depeng Jin, and Yong Li. Physics-infused Machine Learning for Crowd Simulation, in KDD 2022.
(KDD)
PDF
- Shuodi Hui, Huandong Wang, Zhenhua Wang, and Xinghao Yang, Zhongjin Liu, Depeng Jin, and Yong Li. Knowledge Enhanced GAN for IoT Traffic Generation, in The WebConf 2022.
(WWW2022)
Code
PDF
- Tong Xia, Yunhan Qi, Jie Feng, Fengli Xu, Funing Sun, Diansheng Guo, and Yong Li. AttnMove: History Enhanced Trajectory Recovery via Attentional Network, in AAAI 2021.
(AAAI)
Code
PDF
- Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, and Yan Liu. Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network, in ICDE 2020 (short paper).
(ICDE)
PDF
- Sirui Song, Zefang Zong, Yong Li, Xue Liu, and Yang Yu. Reinforced Epidemic Control: Saving Both Lives and Economy, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Qianyue Hao, Lin Chen, Fengli Xu, and Yong Li. Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Jie Feng, Zeyu Yang, Fengli Xu, Haisu Yu, Mudan Wang, and Yong Li. Learning to Simulate Human Mobility, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Zefang Zong, Jie Feng, Kechun Liu, Hongzhi Shi, and Yong Li. DeepDPM: Dynamic Population Mapping via Deep Neural Network, in AAAI 2019.
(AAAI)
PDF
- Jie Feng, Yong Li , Chao Zhang , Funing Sun , Fanchao Meng , Ang Guo, and Depeng Jin. DeepMove: Predicting Human Mobility with Attentional Recurrent Networks, in WWW 2018.
(WWW)
Code
PDF
- Tong Li, Shuodi Hui, Shiyuan Zhang, Huandong Wang, Yuheng Zhang, Pan Hui, Depeng Jin and Yong Li. Mobile User Traffic Generation via Multi-Scale Hierarchical GAN, in TKDD 2024. (TKDD 2024)
- Fengli Xu, Qi Wang, Esteban Moro, Lin Chen, Arianna Salazar Miranda, Marta C. Gonzalez, Michele Tizzoni, Chaoming Song, Carlo Ratti, Luis Bettencourt, Yong Li, and James Evans. Mobility behaviour data quantifies experienced inequalities in urban space, in Nature Human Behaviour, 9, 654–664 (2025). (Nat. Hum. Behav.)
- Can Rong, Jingtao Ding, Yan Liu, Yong Li. A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation, in International Conference on Learning Representations 2025.
(ICLR 2025)
Code
- Xiaochong Lan, Jie Feng, Jiahuan Lei, Xinlei Shi, Yong Li. Benchmarking and Advancing Large Language Models for Local Life Services, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025. (KDD 2025)
- Qingyue Long, Yuan Yuan, Yong Li. A Universal Model for Human Mobility Prediction, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025.
(KDD 2025)
Code
- Jingwei Wang, Qianyue Hao, Wenzhen Huang,Xiaochen Fan, Qin Zhang, Zhentao Tang, Bin Wang, Jianye Hao, Yong Li. CoopRide: Cooperate All Grids in City-Scale Ride-Hailing Dispatching with Multi-Agent Reinforcement Learning, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025.
(KDD 2025)
Code
- Jinwei Zeng, Yu Liu, Guozhen Zhang, Jingtao Ding, Yuming Lin, Jian Yuan, Yong Li. OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data, in International Joint Conference on Artificial Intelligence 2025.
(IJCAI 2025)
Code
- Zhi Sheng, Daisy Yuan, Jingtao Ding, Qi Yan, Xi Zheng, Yue Sun, Yong Li. Unveiling the Power of Noise Priors: Enhancing Diffusion Models for Mobile Traffic Prediction, in International Joint Conference on Artificial Intelligence 2025.
(IJCAI 2025)
Code
- Jie Feng, Yuwei Du, Jie Zhao, Yong Li. AgentMove: A Large Language Model based Agentic Framework for Zero-shot Next Location Prediction, in 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics.
(NAACL 2025)
Code
- Chang Liu, Huan Yan, Hongjie Sui, Haomin Wen, Yuan Yuan, Yuyang Han, Hongsen Liao, Xuetao Ding, Jinghua Hao, Yong Li. MRGRP: Empowering Courier Route Prediction in Food Delivery Service with Multi-Relational Graph, in International World Wide Web Conference 2025. (WWW 2025)
- Yunke Zhang, Ruolong Ma, Xin Zhang, Yong Li. Perceiving Urban Inequality from Imagery Using Visual Language Models with Chain-of-Thought Reasoning, in International World Wide Web Conference 2025.
(WWW 2025)
Code
- Yunke Zhang, Yuming Lin, Guanjie Zheng, Yu Liu, Nicholas Sukiennik, Fengli Xu, Yongjun Xu, Feng Lu, Qi Wang, Yuan Lai, Li Tian, Nan Li, Dongping Fang, Fei Wang, Tao Zhou, Yong Li, Yu Zheng, Zhiqiang Wu, and Huadong Guo. MetaCity: Data-driven sustainable development of complex cities, in The Innovation.
(The Innovation)
PDF
- Yuan Yuan*, Chenyang Shao*, Jingtao Ding, Depeng Jin, Yong Li. Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation, in The Twelfth International Conference on Learning Representations, 2024. (ICLR 2024)
- Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li. UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction, in KDD 2024.
(KDD 2024)
Code
- Hongyuan Su, Yu Zheng, Jingtao Ding, Depeng Jin, Yong Li. MetroGNN: Metro Network Expansion with Reinforcement Learning, in WWW 2024.
(WWW 2024)
Code
- Fengli Xu, Yong Li, Depeng Jin, Jianhua Lu, and Chaoming Song. Emergence of urban growth patterns from human mobility behavior, in Nature Computational Science,1, 791–800.
(Nat. Comp. Sci.)
Code
PDF
- Lin Chen, Yong Li, and Pan Hui. VulnerabilityMap: An Open Framework for Mapping Vulnerability among Urban Disadvantaged Populations in the United States, in IJCAI 2024.
(IJCAI 2024)
Code
- Yuming Lin+, Xin Zhang+, Yu Liu, Zhenyu Han, Qingmin Liao, Yong Li. Long-term Detection and Monitory of Chinese Urban Village Using Satellite Imagery, in IJCAI 2024.
(IJCAI 2024)
Code
PDF
- Yunke Zhang, Fengli Xu, Lin Chen, Yuan Yuan, James Evans, Luis Bettencourt, Yong Li. Counterfactual Mobility Network Embedding Reveals Prevalent Accessibility Gaps in U.S. Cities, in Humanities & Social Sciences Communications,11(1), 1-12.
(HSSCOMMS)
Code
PDF
- 刘家臻，王寰东，丁璟韬，颜欢，徐丰力，范长俊，李勇，刘忠. 人工智能时代下的复杂网络研究.
PDF
- Yu Zheng, Yuming Lin, Liang Zhao, Tinghai Wu, Depeng Jin, Yong Li. Spatial Planning of Urban Communities via Deep Reinforcement Learning, in Nature Computational Science,3(9),748-762.
(Nat. Comp. Sci)
Code
PDF
- Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin and Yong Li. Spatio-temporal Diffsuion Point Processes, in KDD 2023.
(KDD 2023)
Code
PDF
- Yu Zheng, Hongyuan Su, Jingtao Ding, Depeng Jin and Yong Li. Road Planning for Slums via Deep Reinforcement Learning, in KDD 2023.
(KDD 2023)
Code
PDF
- Qingyue Long, Huandong Wang, Tong Li, Lisi Huang, Kun Wang, Qiong Wu, Guangyu Li, Yanping Liang, Li Yu and Yong Li. Practical Synthetic Human Trajectories Generation Based on Variational Point Processes, in KDD 2023.
(KDD 2023)
Code
PDF
- Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, and Yong Li. Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network, in KDD 2023.
(KDD 2023)
Code
PDF
- Hongzhi Shi, Quanming Yao, and Yong Li. Learning to Simulate Crowd Trajectories with Graph Networks, in The WebConf 2023. (WWW2023)
- Hongzhi Shi, Jingtao Ding, Yufan Cao, Quanming Yao, Li Liu, Yong Li. Learning Symbolic Models for Graph-structured Physical Mechanism, in ICLR 2023. (ICLR 2023)
- Zhilun Zhou, Yu Liu, Jingtao Ding, Depeng Jin and Yong Li. Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network, in The WebConf 2023.
(WWW2023)
Code
PDF
- Yuan Yuan, Huandong Wang, Jingtao Ding, Depeng Jin, and Yong Li. Learning to Simulate Daily Activities via Modeling Dynamic Human Needs, in The WebConf2023.
(WWW2023)
PDF
- Huandong Wang, Changzheng Gao, Yuchen Wu, Depeng Jin, Lina Yao, Yong Li. PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning, in AAAI Conference on Artificial Intelligence.
(AAAI)
Code
PDF
- Yuan Yuan, Jingtao Ding, Huandong Wang, Depeng Jin, and Yong li. Activity Trajectory Generation via Modeling Spatiotemporal Dynamics, in KDD 2022（health day）.
(KDD)
Code
PDF
- Qianyue Hao, Wenzhen Huang, Fengli Xu, Kun Tang, and Yong Li. Reinforcement Learning Enhances the Experts: Large-scale COVID-19 Vaccine Allocation with Multi-factor Contact Network, in KDD 2022（health day）.
(KDD)
Code
PDF
- Mudan Wang, Huan Yan, Hongjie Sui, Fan Zuo, Yue Liu, and Yong Li.. Learning to Discover Causes of Traffic Congestion with Limited Labeled Data, in KDD 2022.
(KDD)
PDF
- Fudan Yu, Wenxuan Ao, Huan Yan, Guozhen Zhang, Wei Wu, and Yong Li. Spatio-Temporal Vehicle Trajectory Recovery on Road Network Based on Traffic Camera Video Data, in KDD 2022.
(KDD)
Code
PDF
- Zefang Zong, Hansen Wang, Jingwei Wang, Meng Zheng , and Yong Li. RBG: Hierarchically Solving Large-Scale Routing Problems in Logistic Systems via Reinforcement Learning, in KDD 2022.
(KDD)
PDF
- Tao Feng, Tong Xia, Xiaochen Fan, Huandong Wang, Zefang Zong, and Yong Li. Precise Mobility Intervention for Epidemic Control Using Unobservable Information via Deep Reinforcement Learning, in KDD 2022.
(KDD)
PDF
- Yanxin Xi, Tong Li, Huandong Wang, Yong Li, Sasu Tarkoma, and Pan Hui. Beyond the First Law of Geography: Learning Representations ofSatellite Imagery by Leveraging Point-of-Interests, in The WebConf 2022.
(WWW2022)
Code
PDF
- Yunke zhang, Fengli Xu, Tong Xia, and Yong Li. Quantifying the Causal Effect of Individual Mobility on Health Status in Urban Space, in ACM UbiComp 2021 (IMWUT).
(UbiComp)
PDF
- Wang, Huandong, Qiaohong Yu, Yu Liu, Depeng Jin, and Yong Li. Spatio-Temporal Urban Knowledge Graph Enabled Mobility Prediction, in ACM UbiComp 2021 (IMWUT).
(UbiComp)
PDF
- Zhenyu Han, Haohan Fu, Fengli Xu, Zhen Tu, Yang Yu, Pan Hui, and Yong Li. Who Will Survive and Revive Undergoing the Epidemic: Analyses about POI Visit Behavior in Wuhan via Check-in Records, in ACM UbiComp 2021 (IMWUT).
(UbiComp)
PDF
- Tong Xia, Yunhan Qi, Jie Feng, Fengli Xu, Funing Sun, Diansheng Guo, and Yong Li. AttnMove: History Enhanced Trajectory Recovery via Attentional Network, in AAAI 2021.
(AAAI)
Code
PDF
- Zongyu Lin, Shiqing Lyu, Hancheng Cao, Fengli Xu, Yuqiong Wei, Pan Hui, Hanan Samet, and Yong Li. HealthWalks: Sensing Fine-grained Individual Health Condition via Mobility Data, in ACM UbiComp 2021 (IMWUT).
(UbiComp)
PDF
- Yunke Zhang, Fengli Xu, Tong Li, Vassilis Kostakos, Pan Hui, and Yong Li. Passive Health Monitoring using Large Scale Mobility Data, in ACM UbiComp 2021 (IMWUT).
(UbiComp)
PDF
- Yali Fan, Zhen Tu, Yong Li, Xiang Chen, Hui Gao, Lin Zhang, Li Su, and Depeng Jin. Personalized Context-aware Collaborative Online Activity Prediction, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Jingtao Ding, Guanghui Yu, Yong Li, Depeng Jin, and Hui Gao. Learning from Hometown and Current City: POI Recommendation for Cross-city Travelers via Leveraging User Interest Drift and Transfer, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, and Yan Liu. Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network, in ICDE 2020 (short paper).
(ICDE)
PDF
- Jie Feng, Can Rong, Funing Sun, Siansheng Guo, and YongLi. PMF: A Privacy-preserving Human Mobility Prediction Framework via Federated Learning, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Tong Li, Mingyang Zhang, Hancheng Cao, Yong Li, Sasu Tarkoma, and Pan Hui. "What Apps Did You Use?": Understanding the Long-term Evolution of Mobile App Usage, in WWW 2020, long paper.
(WWW)
PDF
- Di Wu, Tao Xiao, Xuewen Liao, Jie Luo, Chao Wu, Shigeng Zhang, Yong Li, and Yike Guo. When Sharing Economy Meets IoT: Towards Fine-grained Urban Air Quality Monitoring through Mobile Crowdsensing on Bike-share System, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Mingyang Zhang, Tong Li, Yong Li, and Pan Hui. Multi-View Joint Graph Representation Learning for Urban Region Embedding, in IJCAI 2020.
(IJCAI)
Code
PDF
- Jie Feng, Ziqian Lin, Tong Xia, Funing Sun, Diansheng Guo, and Yong Li. A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling, in IJCAI 2020.
(IJCAI)
PDF
- Zhilong Chen, Hancheng Cao, Huandong Wang, Fengli Xu, Vassilis Kostakos, and YongLi. Will You Come Back / Check-in Again? Understanding Characteristics Leading to Urban Revisitation and Re-check-in, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Fengli Xu, Zongyu Lin, TongXia, Diansheng Guo, and YongLi. SUME: Semantic-enhanced Urban Mobility Network Embedding for User Demographic Inference, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Yue Yu, Tong Xia, Huandong Wang, Jie Feng, and Yong Li. Semantic-aware Spatio-temporal App Usage Representation via Graph Convolutional Network, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Sirui Song, Zefang Zong, Yong Li, Xue Liu, and Yang Yu. Reinforced Epidemic Control: Saving Both Lives and Economy, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Qianyue Hao, Lin Chen, Fengli Xu, and Yong Li. Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Jie Feng, Zeyu Yang, Fengli Xu, Haisu Yu, Mudan Wang, and Yong Li. Learning to Simulate Human Mobility, in KDD 2020 (ai for covid).
(KDD)
Code
PDF
- Fengli Xu, Yong Li, and Shusheng Xu. Attentional Multi-graph Convolutional Network for Regional Economy Prediction with Open Migration Data, in KDD 2020 (research track).
(KDD)
PDF
- Hancheng Cao, Zhilong Chen, Fengli Xu, YongLi, and Vassilis Kostakos. Revisitation in Urban Space vs. Online: a Comparison Across POIs, Websites, and Smartphone Apps, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Zefang Zong, Jie Feng, Kechun Liu, Hongzhi Shi, and Yong Li. DeepDPM: Dynamic Population Mapping via Deep Neural Network, in AAAI 2019.
(AAAI)
PDF
- Ziqian Lin, Jie Feng, Ziyang Lu, Yong Li, and Depeng Jin. DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis, in AAAI 2019.
(AAAI)
PDF
- Xinlei Chen, Yu Wang, Jiayou He, Shijia Pan, Yong Li, and Pei Zhang. CAP: Context-aware App Usage Prediction with Heterogeneous Graph Embedding, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Huandong Wang, Yong Li, Sihan Zeng, Gang Wang, Pengyu Zhang, Pan Hui, and Depeng Jin. Modeling Spatio-Temporal App Usage for a Large User Population, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Zhen Tu, Yali Fan, YongLi, Xiang Chen, Li Su, and Depeng Jin. From Fingerprint to Footprint: Cold-start Location Recommendation by Learning User Interest from App Data, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Chen Gao, Chao Huang, Yue Yu, Huandong Wang, Yong Li, and Depeng Jin. Privacy-preserving Cross-domain Location Recommendation, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Tong Xia, and Yong Li. Revealing Urban Dynamics by Learning Online and Offline Behaviours Together, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Mingyang Zhang, Tong Li, Hongzhi Shi, Yong Li, and Pan Hui. A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data, in IJCAI 2019.
(IJCAI)
PDF
- Fengli Xu, Zhen Tu, Hongjia Huang, Shuhao Chang, Funing Sun, Diansheng Guo, and Yong Li. No More than What I Post: Preventing Linkage Attacks on Check-in Services, in WWW 2019, short paper.
(WWW)
PDF
- Tong Xia , Yue Yu, Fengli Xu, Funing Sun , Diansheng Guo , Depeng Jin , and Yong Li. Understanding Urban Dynamics via State-sharing Hidden Markov Model, in WWW 2019, short paper.
(WWW)
Code
PDF
- Jie Feng , Mingyang Zhang , Huandong Wang , Zeyu Yang , Chao Zhang , Yong Li, and Depeng Jin. DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data, in WWW 2019, long paper.
(WWW)
Code
PDF
- Hongzhi Shi , Chao Zhang , Quanming Yao , Yong Li , Funing Sun, and Depeng Jin. State-Sharing Sparse Hidden Markov Models for Personalized Sequences, in KDD 2019, research track, oral paper.
(KDD)
PDF
- Jie Feng, Yong Li , Chao Zhang , Funing Sun , Fanchao Meng , Ang Guo, and Depeng Jin. DeepMove: Predicting Human Mobility with Attentional Recurrent Networks, in WWW 2018.
(WWW)
Code
PDF
- Zhen Tu, Runtong Li, Yong Li, Gang Wang, Di Wu, Pan Hui, Li Su, and Depeng Jin. Your Apps Give You Away: Distinguishing Smartphone Users by Their App Usage Behaviors, in ACM UbiComp 2018 (IMWUT), Distinguished Paper Award.
(UbiComp)
PDF
- Hancheng Cao, Jie Feng, Yong Li, and Vassilis Kostakos. Uniqueness in the City: Urban Morphology and Location Privacy, in ACM UbiComp 2018 (IMWUT).
(UbiComp)
PDF
- Fengli Xu, Guozhen Zhang, Zhilong Chen, Jiaxin Huang,Yong Li, Diyi Yang, BenY. Zhao, and Fanchao Meng. Understanding Motivations behind Inaccurate Check-ins, in CSCW 2018.
(CSCW)
PDF
- Fudan Yu, Huan Yan, Rui Chen, Guozhen Zhang, Meng Chen, Yong Li. City-scale Vehicle Trajectory Data From Traffic Camera Videos, in Scientific Data,10(1),711. (Sci Data)
- Yanxin Xi, Yu Liu, Tong Li, Jingtao Ding, Yunke Zhang, Sasu Tarkoma, Yong Li, Pan Hui. A Satellite Imagery Dataset for Long-Term Sustainable Development in United States Cities, in Scientific data,10(1),866. (Sci Data)
- Yunke Zhang, Daoping Wang, Yu Liu, Kerui Du, Peng Lu, Pan He, and Yong Li. Urban food delivery services as extreme-heat adaptation, in Nature Cities 2, 170-179(2025).
(Nat. Cities)
Code
PDF
- Yunke Zhang , Yiran Fan, Peijie Liu, Fengli Xu, Yong Li. Cyber Food Swamps: Investigating the Impacts of Online-to-Offline Food Delivery Platforms on Healthy Food Choices, in International AAAI Conference on Web and Social Media 2025.
(ICWSM 2025)
Code
PDF
- Zhilong Chen, Yong Li. The Sharply Decreasing Disruptiveness of HCI., in Conference on Human Factors in Computing Systems 2025. (CHI 2025)
- Chang Liu, Jingtao Ding, Yiwen Song, Yong Li. TDNetGen: Empowering complex network resilience prediction with generative augmentation of topology and dynamics, in KDD 2024.
(KDD 2024)
Code
- Lin Chen, Fengli Xu, Zhenyu Han, Kun Tang, Pan Hui, James Evans, Yong Li. Strategic COVID-19 vaccine distribution can simultaneously elevate social utility and equity, in Nature Human Behaviour,6(11),1503-1514.
(NHB 2022)
Code
PDF
- Fengli Xu, Yong Li, Depeng Jin, Jianhua Lu, and Chaoming Song. Emergence of urban growth patterns from human mobility behavior, in Nature Computational Science,1, 791–800.
(Nat. Comp. Sci.)
Code
PDF
- Xiaochong Lan, Chen Gao, Depeng Jin, Yong Li. Stance Detection with Collaborative Role-Infused LLM-Based Agents, in ICWSM 2024.
(ICWSM 2024)
Code
- Xiaochong Lan, Chen Gao, Depeng Jin, Yong Li. Stance Detection with Collaborative Role-Infused LLM-Based Agents, in International AAAI Conference on Web and Social Media.
(ICWSM 2024)
Code
PDF
- Yunke Zhang, Fengli Xu, Lin Chen, Yuan Yuan, James Evans, Luis Bettencourt, Yong Li. Counterfactual Mobility Network Embedding Reveals Prevalent Accessibility Gaps in U.S. Cities, in Humanities & Social Sciences Communications,11(1), 1-12.
(HSSCOMMS)
Code
PDF
- 刘家臻，王寰东，丁璟韬，颜欢，徐丰力，范长俊，李勇，刘忠. 人工智能时代下的复杂网络研究.
PDF
- Jinghua Piao, Jiazhen Liu, Fang Zhang, Jun Su, and Yong Li.. Human-AI Adaptive Dynamics Drive Emergence of Information Cocoons, in Nature Machine Intellgence,5(11),1214-1224.
(Nat. Mach. Intell)
Code
PDF
- Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan and Yong Li. GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning, in KDD 2023.
(KDD 2023)
Code
PDF
- Yu Liu, Xin Zhang, Jingtao Ding, Yanxin Xi and Yong Li. Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction, in The WebConf 2023.
(WWW2023)
Code
PDF
- Zhilong Chen, Hancheng Cao, Xiaochong Lan, Zhicong Lu, and Yong Li. Beyond Virtual Bazaar: How Social Commerce Promotes Inclusivity for the Traditionally Underserved Community in Chinese Developing Regions, in CHI 2022.
(CHI)
PDF
- Guozhen Zhang, Jinwei Zeng, Zhengyue Zhao, Depeng Jin, and Yong Li. A Counterfactual Modeling Framework for Churn Prediction, in The ACM Web Search and Data Mining Conference.
(WSDM)
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- Hancheng Cao, Zhilong Chen, Mengjie Cheng, Shuling Zhao, Tao Wang, and YongLi. You Recommend, I Buy: How and Why People Engage in Instant Messaging Based Social Commerce, in CSCW 2021.
(CSCW)
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- Jinghua Piao, Guozhen Zhang, Fengli Xu, Zhilong Chen, and Yong Li. Predicting Customer Value with Social Relationships via Motif-based Graph Attention Networks, in WWW 2021.
(WWW)
Code
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- Guozhen Zhang, Yong Li, Yuan Yuan, Fengli Xu, Hancheng Cao, Yujian Xu, and Depeng Jin. Community Value Prediction in Social E-commerce, in WWW 2021.
(WWW)
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- Zhilong Chen, Hancheng Cao, Yuting Deng, Xuan Gao, Jinghua Piao, Fengli Xu, Yu Zhang, and Yong Li. Learning from Home: A Mixed-Methods Analysis of Live Streaming Based Remote Education Experience in Chinese Colleges during the COVID-19 Pandemic, in CHI 2021.
(CHI)
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- Fengli Xu, Guozhen Zhang, Yuan Yuan, Huandong Wang, Diyi Yang, Depeng Jin, and Yong Li. Would You Like to Join Us: Understanding the Invitation Acceptance in Agent-initiated Social E-commerce, in ICWSM 2021.
(ICWSM)
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- Jun Zhang, Chen Gao, Depeng Jin, and Yong Li. Group-Buying Recommendation for Social E-Commerce, in ICDE 2021.
(ICDE)
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- Hancheng Cao, Zhilong Chen, Fengli Xu, Tao Wang, Yujian Xu, Lianglun Zhang, and Yong Li. When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian, in ICWSM 2020.
(ICWSM)
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- Tong Li, Mingyang Zhang, Hancheng Cao, Yong Li, Sasu Tarkoma, and Pan Hui. "What Apps Did You Use?": Understanding the Long-term Evolution of Mobile App Usage, in WWW 2020, long paper.
(WWW)
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- Zhilong Chen, Hancheng Cao, Huandong Wang, Fengli Xu, Vassilis Kostakos, and YongLi. Will You Come Back / Check-in Again? Understanding Characteristics Leading to Urban Revisitation and Re-check-in, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
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- Zhilong Chen, Hancheng Cao, Fengli Xu, Mengjie Cheng, Tao Wang, and Yong Li. Understanding the Role of Intermediaries in Online Social E-commerces: an Exploratory Study of Beidian, in CSCW 2020.
(CSCW)
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- Yuxuan Yan, Zhenhua Li, Qi Alfred Chen, Christo Wilson, Tianyin Xu, Ennan Zhai, Yong Li, and Yunhao Liu. Understanding and Detecting Overlay-based Android Malware at Market Scales, in MobiSys 2019.
(MobiSys)
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- Fengli Xu, Zhen Tu, Hongjia Huang, Shuhao Chang, Funing Sun, Diansheng Guo, and Yong Li. No More than What I Post: Preventing Linkage Attacks on Check-in Services, in WWW 2019, short paper.
(WWW)
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- Tzu-Heng Lin, Chen Gao, and Yong Li. CROSS: Cross-platform Recommendation for Online Shopping in Social Media, in SIGIR 2019, long paper.
(SIGIR)
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- Fengli Xu, Zhenyu Han, Jinghua Piao, and Yong Li. "I Think You’ll Like It": Modelling the Online Purchase Behavior in Social E-commerce, in CSCW 2019.
(CSCW)
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- Fengli Xu, Guozhen Zhang, Zhilong Chen, Jiaxin Huang,Yong Li, Diyi Yang, BenY. Zhao, and Fanchao Meng. Understanding Motivations behind Inaccurate Check-ins, in CSCW 2018.
(CSCW)
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- Pengyang Shao, Yonghui Yang, Chen Gao, Lei Chen, Kun Zhang, Chenyi Zhuang, Le Wu, Yong Li, Meng Wang. Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025. (KDD 2025)
- Zhiqiang Pan, Chen Gao, Fei Cai, Wanyu Chen, Xin Zhang, Honghui Chen, Yong Li. On the Cross-Graph Transferability of Dynamic Link Prediction, in International World Wide Web Conference 2025.
(WWW 2025)
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- Yu Shang, Chen Gao, Nian Li, Yong Li.. A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform, in International World Wide Web Conference 2025.
(WWW 2025)
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- Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li. Inverse Learning with Extremely Sparse Feedback for Recommendation, in AAAI Conference on Artificial Intelligence 2025.
(AAAI 2025)
Code
- Yuan Yuan*, Chenyang Shao*, Jingtao Ding, Depeng Jin, Yong Li. Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation, in The Twelfth International Conference on Learning Representations, 2024. (ICLR 2024)
- Lin Chen, Fengli Xu, Nian Li, Zhenyu Han, Meng Wang, Yong Li, Pan Hui. Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network, in 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
(KDD 2024)
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- Jiahui Gong, Jingtao Ding, Fanjin Meng, Guilong Chen, Hong Chen, Shen Zhao, Haisheng Lu, Yong Li. A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction, in 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (KDD 2024)
- Nicholas Sukiennik, Chen Gao, Nian Li. Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation, in WWW 2024. (WWW 2024)
- Yu Shang, Chen Gao, Jiansheng Chen, Depeng Jin, Yong Li. Improving Item-side Fairness of Multimodal Recommendation via Modality Debiasing, in WWW 2024.
(WWW 2024)
Code
- Nian Li, Yunzhu Pan, Chen Gao, Depeng Jin, Qingmin Liao. Full-stage Diversified Recommendation: Large-scale Online Experiments in Short-video Platform, in International World Wide Web Conference 2024. (WWW 2024)
- Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang. Mixed Attention Network for Cross-domain Sequential Recommendation, in WSDM 2024.
(WSDM 2024)
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- Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li. Inverse Learning with Extremely Sparse Feedback for Recommendation, in WSDM 2024.
(WSDM 2024)
Code
- Nian Li, Xin Ban, Cheng Ling, Chen Gao, Lantao Hu, Peng Jiang, Kun Gai, Yong Li, Qingmin Liao. Modeling User Fatigue for Sequential Recommendation, in SIGIR 2024.
(SIGIR 2024)
Code
- Nian Li, Xin Ban, Cheng Ling, Chen Gao, Lantao Hu, Peng Jiang, Kun Gai, Yong Li, Qingmin Liao. Modeling User Fatigue for Sequential Recommendation, in SIGIR 2024.
(SIGIR 2024)
Code
- Jinghua Piao, Jiazhen Liu, Fang Zhang, Jun Su, and Yong Li.. Human-AI Adaptive Dynamics Drive Emergence of Information Cocoons, in Nature Machine Intellgence,5(11),1214-1224.
(Nat. Mach. Intell)
Code
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- Xiaochong Lan, Chen Gao, Shiqi Wen, Xiuqi Chen, Yingge Che, Han Zhang, Huazhou Wei, Hengliang Luo, Yong Li. NEON: Living Needs Prediction System in Meituan, in KDD 2023.
(KDD 2023)
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- Yan Wen, Chen Gao, Lingling Yi, Liwei Qiu, Yaqing Wang, Yong Li. Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering, in KDD 2023. (KDD 2023)
- Yancheng Dong, Zhenyang Li, Chen Gao, Yizhou Zhao, Dong Li, Jianye Hao, Zhi Wang, Kai Zhang and Yong Li. Breaking Filter Bubble: A Reinforcement Learning Framework of Controllable Recommender System, in The WebConf 2023. (WWW2023)
- Yu Liu, Xin Zhang, Jingtao Ding, Yanxin Xi and Yong Li. Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction, in The WebConf 2023.
(WWW2023)
Code
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- Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin and Yong Li. Robust Preference-Guided Denoising for Graph based Social Recommendation, in The WebConf 2023.
(WWW2023)
Code
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- Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Zhiheng Li, Depeng Jin and Yong Li. Dual-interest Factorization-heads Attention for Sequential Recommendation, in The WebConf 2023.
(WWW2023)
Code
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- Yinfeng Li, Chen Gao, Xiaoyi Du, Huazhou Wei, Hengliang Luo, Depeng Jin, and Yong Li. Automatically Discovering User Consumption Intents in Meituan, in KDD 2022. (KDD)
- Chang Liu, Chen Gao, Yuan Yuan, Chen Bai, Lingrui Luo, Xiaoyi Du, Xinlei Shi, Hengliang Luo, Depeng Jin and Yong Li. Modeling the Effect of Persuasion Factor on User Decision for Recommendation, in KDD 2022.
(KDD)
Code
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- Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang and Yong Li. A Review-aware Graph Contrastive Learning Framework for Recommendation, in SIGIR 2022. (SIGIR)
- Yinfeng Li, Chen Gao, Hengliang Luo, Depeng Jin and Yong Li. Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation, in SIGIR 2022. (SIGIR)
- Guanyu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin and Yong Li. Dual Contrastive Network for Sequential Recommendation, in SIGIR 2022.
(SIGIR)
Code
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- Yu Zheng, Chen Gao, Jianxin Chang, Yannan Niu, Yang Song, Depeng Jin, and Yong Li. Disentangling Long and Short-Term Interests for Recommendation, in The WebConf 2022.
(WWW2022)
Code
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- Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang Song, Depeng Jin, and Yong Li. Sequential Recommendation with Graph Convolutional Networks, in SIGIR 2021. (SIGIR)
- Yukun Ping, Chen Gao, Taichi Liu, Xiaoyi Du, Hengliang Luo, Depeng Jin, and Yong Li. User Consumption Intention Prediction in Meituan, in KDD 2021.
(KDD)
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- Qianyue Hao, Feling Xu, Lin Chen, Pan Hui, and Yong Li. Hierarchical Reinforcement Learning for Scarce Medical Resource Allocation with Imperfect Information, in KDD 2021.
(KDD)
Code
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- Chen Gao, Quanming Yao, Depeng Jin, and Yong Li. Efficient Data-specific Model Search for Collaborative Filtering, in KDD 2021. (KDD)
- Yu Liu, Quanming Yao, and Yong Li. Role-Aware Modeling for N-ary Relational Knowledge Bases, in WWW 2021.
(WWW)
Code
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- Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, and Yong Li. DGCN: Diversified Recommendation with Graph Convolutional Networks, in WWW 2021.
(WWW)
Code
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- Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, and Yong Li. Disentangling User Interest and Conformity for Recommendation with Causal Embedding, in WWW 2021.
(WWW)
Code
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- Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, and Yong Li. Learning Embedding Sizes for Recommender Systems, in ICLR 2021.
(ICLR)
Code
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- Jun Zhang, Chen Gao, Depeng Jin, and Yong Li. Group-Buying Recommendation for Social E-Commerce, in ICDE 2021.
(ICDE)
Code
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- Jingtao Ding, Guanghui Yu, Yong Li, Depeng Jin, and Hui Gao. Learning from Hometown and Current City: POI Recommendation for Cross-city Travelers via Leveraging User Interest Drift and Transfer, in ACM UbiComp 2020 (IMWUT).
(UbiComp)
PDF
- Yu Zheng, Chen Gao, Xiangnan He, Yong Li, and Depeng Jin. Price-aware Recommendation with Graph Convolutional Networks, in ICDE 2020 (long paper).
(ICDE)
PDF
- Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li, and Cho-Jui Hsieh. Efficient Neural Interaction Function Search for Collaborative Filtering, in WWW 2020, long paper.
(WWW)
Code
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- Yu Liu, Quanming Yao, and Yong Li. Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases, in WWW 2020, long paper.
(WWW)
Code
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- Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin, and Yong Li. Bundle Recommendation with Graph Convolutional Networks, in SIGIR 2020 (short paper).
(SIGIR)
Code
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- Bowen Jin, Chen Gao, Xiangnan He, Depeng Jin, and Yong Li. Multi-behavior Recommendation with Graph Convolution Networks, in SIGIR 2020 (long paper).
(SIGIR)
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- Chen Gao, Chao Huang, Dongsheng Lin, Depeng Jin, and Yong Li. DPLCF: Differentially Private Local Collaborative Filtering, in SIGIR 2020 (long paper).
(SIGIR)
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- Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, and Depeng Jin. Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering, in NeurIPS 2020.
(NeurIPS)
Code
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- Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, and Depeng Jin. Neural Multi-task Recommendation from Multi-behavior Data, in ICDE 2019.
(ICDE)
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- Zhen Tu, Yali Fan, YongLi, Xiang Chen, Li Su, and Depeng Jin. From Fingerprint to Footprint: Cold-start Location Recommendation by Learning User Interest from App Data, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Chen Gao, Chao Huang, Yue Yu, Huandong Wang, Yong Li, and Depeng Jin. Privacy-preserving Cross-domain Location Recommendation, in ACM UbiComp 2019 (IMWUT).
(UbiComp)
PDF
- Huan Yan, Xiangning Chen, Chen Gao, Yong Li, and Depeng Jin. DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation, in IJCAI 2019.
(IJCAI)
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- Jingtao Ding, Yuhan Quan, Xiangnan He, Yong Li, and Depeng Jin. Reinforced Negative Sampling for Recommendation with Exposure Data, in IJCAI 2019.
(IJCAI)
Code
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- Chen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li, and Depeng Jin. Cross-domain Recommendation Without Sharing User-relevant Data, in WWW 2019, long paper.
(WWW)
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- Jie Feng , Mingyang Zhang , Huandong Wang , Zeyu Yang , Chao Zhang , Yong Li, and Depeng Jin. DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data, in WWW 2019, long paper.
(WWW)
Code
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- Tzu-Heng Lin, Chen Gao, and Yong Li. CROSS: Cross-platform Recommendation for Online Shopping in Social Media, in SIGIR 2019, long paper.
(SIGIR)
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- Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, and Yue Wang. λOpt: Learn to Regularize Recommender Models in Finer Levels, in KDD 2019, research track, oral paper.
(KDD)
Code
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- Jingtao Ding , Fuli Feng , Xiangnan He , Guanghui Yu , Yong Li, and Depeng Jin. An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data, in WWW 2018 Poster, Best Poster Paper Award.
(WWW)
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- Jingtao Ding , Guanghui Yu , Xiangnan He , Yuhan Quan , Yong Li , Tat-Seng Chua , Depeng Jin, and Jiajie Yu. Improving Implicit Recommender Systems with View Data, in IJCAI 2018.
(IJCAI)
Code
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- Yu Shang, Yu Li, Keyu Zhao, Likai Ma, Jiahe Liu, Fengli Xu, Yong Li.. AgentSquare: Automatic LLM Agent Search in Modular Design Space, in International Conference on Learning Representations 2025.
(ICLR 2025)
Code
- Peijie Liu, Fengli Xu, Yong Li. Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models, in International Conference on Machine Learning 2025.
(ICML 2025)
Code
- Jie Feng*, Jun Zhang*, Tianhui Liu*, Xin Zhang, Tianjian Ouyang, Junbo Yan, Yuwei Du, Siqi Guo, Yong Li. CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025.
(KDD 2025)
Code
- Jie Feng*, Tianhui Liu*, Yuwei Du, Siqi Guo, Yuming Lin, Yong Li. CityGPT: Empowering Urban Spatial Cognition of Large Language Models, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025.
(KDD 2025)
Code
- Fanhang Man, Huandong Wang, Jianjie Fang, Zhaoyi Deng, Baining Zhao, Xinlei Chen, and Yong Li. Context-Aware Sentiment Forecasting via LLM-based Multi-Perspective Role-Playing Agents, in Annual Meeting of the Associa-tion for Computational Linguistics 2025. (ACL 2025)
- Xiaochong Lan, Jie Feng, Yizhou Sun, Chen Gao, Jiahuan Lei, Xinleishi, Hengliang Luo, Yong Li. Open-Set Living Need Prediction with Large Language Models, in Annual Meeting of the Associa-tion for Computational Linguistics 2025 Findings. (ACL 2025 Findings)
- Baining Zhao, Jianjie Fang, Zichao Dai, Ziyou Wang, Jirong Zha, Weichen Zhang, Chen Gao, Yue Wang, Jinqiang Cui, Xinlei Chen, Yong Li. Benchmarking Video-Language Models for Embodied Motion Cognition in Urban Open-Ended Spaces, in Annual Meeting of the Associa-tion for Computational Linguistics 2025.
(ACL 2025)
Code
- Weichen Zhang, Chen Gao, Shiquan Yu, Ruiying Peng, Baining Zhao, Qian Zhang, Jinqiang Cui, Xinlei Chen, Yong Li. CityNavAgent: Aerial Vision-and-Language Navigation with Hierarchical Semantic Planning and Global Memory, in Annual Meeting of the Associa-tion for Computational Linguistics 2025. (ACL 2025)
- Wenrui Xu, Dalin Lyu, Weihang Wang, Jie Feng, Chen Gao, Yong Li. Defining and Evaluating Visual Language Models' Basic Spatial Abilities: A Perspective from Psychometrics, in Annual Meeting of the Associa-tion for Computational Linguistics 2025. (ACL 2025)
- Jinghua Piao, Zhihong Lu, Chen Gao and Yong Li. Social Bots Meet Large Language Model: Political Bias and Social Learning Inspired Mitigation Strategies, in International World Wide Web Conference 2025.
(WWW 2025)
Code
- Chenyang Shao, Xinyuan Hu, Yutang Lin, Fengli Xu. Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents, in International World Wide Web Conference 2025.
(WWW 2025)
Code
- Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang. MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector, in AAAI Conference on Artificial Intelligence 2025.
(AAAI 2025)
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- Jinghua Piao,Chen Gao,Fang Zhang,Jun Su ,Yong Li. Large-Scale Social Simulator: Frontiers and Perspectives, in 系统仿真学报. (系统仿真学报)