KDD 2026于2026年8月9日至13日于韩国济州（Jeju, Korea ）正在举行。
本文总结了KDD 2026（February Cycle）上有关时空数据（Spatial-Temporal）的相关论文。
注 ：由于时空数据的论文高达61篇，笔者将分为上下2篇推文来总结，上篇主要涉及交通时空，轨迹，POI等论文，包含Research ，Applied Data Science ，AI for Science 和Datasets and Benchmarks 4个Track的论文。
时空数据Topic：时空（交通）预测，轨迹数据挖掘（表示，生成），POI推荐，ETA，基础模型，大模型，agent的应用等。
KDD 2026(2月轮)：https://kdd2026.kdd.org/papers/#february_cycle
| Research 1. Beyond Language Processing: LLMs Rules-Injected Instruction Tuning for Traffic Prediction 2. Unified Spatio-Temporal Tokens are Bases for Generalizable Traffic Forecasting 3. Eliciting Frequency-Conditioned Spatial Dynamics for Long-Term Spatio-Temporal Forecasting 4. GODM: Graph Orthogonal Diffusion Models for Spatio-Temporal Forecasting 5. Low-Rank Prior-Induced Consistency Flow Matching for Efficient Traffic Imputation 6. Diffusion-based Spatio-temporal Interpolation with Dynamic Sensor Sets 7. EARTH: Accelerating Spatiotemporal Network K-function-based Analytics 8. CausalPOI: Spatio-Temporal Graph-Based Causal Modeling for Cold-Start POI Check-in Forecasting 9. Drift-Aware Memory-Augmented Spatio-Temporal Graph Attention for Industrial Anomaly Detection 10. Orbit-Adaptive Zero-Shot Forecasting on Spatio-Temporal Graph 11. FedTT: A Federated Spatio-Temporal Learning Framework for Cross-City Traffic Knowledge Transfer 12. Invariant Structure Learning with Pre-trained Language Models for Spatio-temporal Graph 13. STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction 14. Orchestrating Reasoning and Reaction: An Asynchronous Hierarchical Framework for LLM-driven Traffic Signal Control 15. HURST: Heterogeneity-Adaptive Urban Foundation Models for Spatiotemporal Prediction via Self-Partitional Mixture-of-Spatial-Experts 16. Mag-Mamba: Modeling Coupled Spatio-temporal Asymmetry for POI Recommendation 17. G²PRO: Gradient-guided Graph Prompt Optimization for LLM-based POI Recommendation 18. Is the Last Check-In All You Need? Next POI Recommendation: Recall and Rerank 19. Towards Robust Travel Time Estimation: An Out-of-Distribution Generalization Approach 20. FairTraj: Density-Aware Generative Data Augmentation for Fairness in Downstream Trajectory Learning Tasks 21. REFINE: Trajectory Representation Learning via Closed-Loop Transcription 22. LATTE: Learning Adaptive Segmentation for Efficient and Effective Trajectory Similarity Learning 23. Road-Constrained Vehicle Trajectory Recovery from Traffic Video Using Spatio-Temporal Voxel Representation 24. On Optimizing Route-Responsive Urban Tree Placement in City-Scale Pedestrian Networks 25. UNITE: A Unified Framework for Accurate and Efficient Origin-Destination and Route Travel Time Estimation Applied Data Science 26. DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments 27. A Data-driven Route Segmentation Framework for Time-of-Arrival Estimation Service AI for Sciences 28. Hybrid Graph Learning Reconstructs Global Ocean Oxygen Spatiotemporal Changes 29. Collaborative Deterministic-Probabilistic Learning for Real-World Spatiotemporal Dynamics 30. MUSTANG: Multi-Variable Spatio-Temporal Meta-Learning for Water Data Imputation 31. UrbanFM: Scaling Urban Spatio-Temporal Foundation Models 32. Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems Datasets and Benchmarks 33. UrbanWell: Benchmarking Multimodal Large Language Models for Spatio-Temporal Urban Wellbeing Analytics 34. AgentCity: An AI-Maintained Continuous Benchmark for Traffic Prediction 35. MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios |
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Research
1 Beyond Language Processing: LLMs Rules-Injected Instruction Tuning for Traffic Prediction
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817854++
代码 ：++https://github.com/tigerbunny2023/RuleGPT++
作者：Weihao Jiang (College of Artificial Intelligence, Zhejiang University,Hikvision Research Institute); Huizhao Wang (Hikvision Research Institute); Zhihui Hu (Hikvision Research Institute); Wenyu Hu (Hikvision Research Institute); Yao Fu (Hikvision Research Institute); Jiang Zhu (Hikvision Research Institute); Jun Xiao (College of Computer Science and Technology, Zhejiang University)
关键词：交通预测，多元异质交通数据挖掘，LLM
2 Unified Spatio-Temporal Tokens are Bases for Generalizable Traffic Forecasting
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817746++
代码 ：++https://github.com/JimmyChen6/STUNet++
作者：Yujun Chen (Zhejiang University); Shihao Tu (SUPCON Technology Co., Ltd.); Wenyue Ding (SUPCON Technology Co., Ltd.); Yicheng Lu (Zhejiang University); Qingkai Ren (Zhejiang University); Yangjie Zheng (Zhejiang University); Yang Yang (Zhejiang University)
关键词：交通预测，Transformer，显式图建模
3 Eliciting Frequency-Conditioned Spatial Dynamics for Long-Term Spatio-Temporal Forecasting
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817629++
代码 ：++https://github.com/luck-seu/FCoSD++
作者：Xigang Sun (Southeast University); Haoyu Chen (Southeast University); Jiahui Jin (Southeast University); Xiangguo Sun (Southeast University)
关键词：长程时空预测，自适应频域分解，空间动态性
4 GODM: Graph Orthogonal Diffusion Models for Spatio-Temporal Forecasting
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817989++
作者：Zhixian Wang (The University of Hong Kong); Michel Ferreira Cardia Haddad (Queen Mary University of London); Jose Eduardo Medina Reyes (Queen Mary University of London); Chenxi Wang (The University of Hong Kong); Yi Wang (The University of Hong Kong)
关键词：时空预测，扩散模型，概率预测
5 Low-Rank Prior-Induced Consistency Flow Matching for Efficient Traffic Imputation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818063++
代码 ：++https://github.com/maoxiaowei97/LOFT++
作者：Xiaowei Mao (School of Computer Science and Technology, Beijing Jiaotong University); Tingrui Wu (School of Computer Science and Technology, Beijing Jiaotong University); Yawen Yang (School of Computer Science and Technology, Beijing Jiaotong University); Shengnan Guo (School of Computer Science and Technology, Beijing Jiaotong University,Key Laboratory of Big Data & Artificial Intelligence in Transportation, Ministry of Education); Yan Lin (Department of Computer Science, Aalborg University); Shilong Zhao (School of Computer Science and Technology, Beijing Jiaotong University); Haochen Lv (School of Computer Science and Technology, Beijing Jiaotong University); Youfang Lin (School of Computer Science and Technology, Beijing Jiaotong University,Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence); Huaiyu Wan (School of Computer Science and Technology, Beijing Jiaotong University,Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence)
关键词：交通插补，流匹配，生成模型
6 Diffusion-based Spatio-temporal Interpolation with Dynamic Sensor Sets
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817811++
作者：Mohammad Rafid Ul Islam (Department of EECS, Oregon State University); Prasad Tadepalli (Department of EECS, Oregon State University); Alan Fern (Department of EECS, Oregon State University)
关键词：时空插值，扩散模型，傅里叶压缩
7 EARTH: Accelerating Spatiotemporal Network K-function-based Analytics
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817706++
代码 ：++https://github.com/edisonchan2013928/EARTH++
作者：Tsz Nam Chan (College of Computer Science and Software Engineering, Shenzhen University); Hongwei Ye (College of Computer Science and Software Engineering, Shenzhen University); Leong Hou U (Department of Computer and Information Science, University of Macau); Yun Peng (School of Artificial Intelligence, Guangzhou University); Dingming Wu (College of Computer Science and Software Engineering, Shenzhen University); Jianliang Xu (Department of Computer Science, Hong Kong Baptist University); Christian S. Jensen (Department of Computer Science, Aalborg University)
关键词：时空网络K函数，复杂度降低方法，正交范围计数问题
8 CausalPOI: Spatio-Temporal Graph-Based Causal Modeling for Cold-Start POI Check-in Forecasting
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817641++
代码 ：++https://github.com/ZZQ-NTU/CausalPOI++
作者：Zhaoqi Zhang (Nanyang Technoogical University); Miao Xie (China Agricultural University); Yi Li (Nanyang Technological University); Linyou Cai (Meituan); Siqiang Luo (Nanyang Technological University); Gao Cong (Nanyang Technological University)
关键词：冷启动POI序列预测，时空图神经网络，因果推荐
9 Drift-Aware Memory-Augmented Spatio-Temporal Graph Attention for Industrial Anomaly Detection
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818125++
作者：Yooshin Kim (Daegu Gyeongbuk Institute of Science and Technology); Donghoon Shin (Daegu Gyeongbuk Institute of Science and Technology)
关键词：多元时序，异常检测，图神经网络，时序推理
10 Orbit-Adaptive Zero-Shot Forecasting on Spatio-Temporal Graph
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817871++
代码 ：++https://github.com/xysparks/OA-GNN++
作者：Yue Xu (University of Macau,Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang University); Wenying Duan (School of Artificial Intelligence, Nanchang University,Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang University); Xiaoxi He (Faculty of Science and Technology, University of Macau); Shuai Ma (School of Artificial Intelligence, Nanchang University)
关键词：时空数据，零样本学习，时空图神经网络
11 FedTT: A Federated Spatio-Temporal Learning Framework for Cross-City Traffic Knowledge Transfer
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818124++
作者：Zhihao Zeng (School of Software Technology, Zhejiang University); Ziquan Fang (School of Software Technology, Zhejiang University); Yuting Huang (School of Software Technology, Zhejiang University); Yujie Fang (School of Software Technology, Zhejiang University); Lu Chen (College of Computer Science and Technology, Zhejiang University)
关键词：交通预测，联盟学习，知识迁移
12 Invariant Structure Learning with Pre-trained Language Models for Spatio-temporal Graph
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818006++
代码 ：++https://github.com/tingwang25/InvSTG-PLM++
作者：Ting Wang (School of Computer Science and Technology, Tongji University,Engineering Research Center of Key Software Technologies for Smart City Perception and Planning, Ministry of Education); Duo Zhou (UIUC); Daqian Shi (Queen Mary University of London); Hao Tang (Peking University); Hao Deng (School of Computer Science and Technology, Tongji University,Engineering Research Center of Key Software Technologies for Smart City Perception and Planning, Ministry of Education); Shengjie Zhao (School of Computer Science and Technology, Tongji University,Engineering Research Center of Key Software Technologies for Smart City Perception and Planning, Ministry of Education)
关键词：时空预测，时空图神经网络，不变学习，稳健预测
13 STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817653++
代码 ：++https://github.com/IfReasonable/STM3_KDD26++
作者：Haolong Chen (Shenzhen International Center for Industrial and Applied Mathematics,Shenzhen Research Institute of Big Data); Liang Zhang (Shenzhen Campus of Sun Yat-sen University); Zhengyuan Xin (Shenzhen Research Institute of Big Data,The Chinese University of Hong Kong, Shenzhen); Guangxu Zhu (Shenzhen International Center for Industrial and Applied Mathematics,Shenzhen Research Institute of Big Data)
关键词：时空序列预测，MoE，选择状态空间
14 Orchestrating Reasoning and Reaction: An Asynchronous Hierarchical Framework for LLM-driven Traffic Signal Control
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818039++
作者：Fansheng Sun (Hong Kong University of Science and Technology (Guangzhou),Xi'an Jiaotong University); Jiyu Wang (Hong Kong University of Science and Technology (Guangzhou)); Zhidan Liu (Hong Kong University of Science and Technology (Guangzhou))
关键词：信号灯控制，LLM，多智能体，强化学习
15 HURST: Heterogeneity-Adaptive Urban Foundation Models for Spatiotemporal Prediction via Self-Partitional Mixture-of-Spatial-Experts
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817747++
代码 ：++https://github.com/zzrDG/HURST++
作者：Zirui Zhou (Harbin Institute of Technology, Shenzhen); Xun Zhou (Harbin Institute of Technology, Shenzhen); Kanyu Bao (Harbin Institute of Technology, Shenzhen); Shengxin Liu (Harbin Institute of Technology, Shenzhen); Kehai Chen (Harbin Institute of Technology, Shenzhen); Min Zhang (Harbin Institute of Technology, Shenzhen)
关键词：时空预测，MoE，基础模型，空间异质性
16 Mag-Mamba: Modeling Coupled Spatio-temporal Asymmetry for POI Recommendation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817697++
代码 ：++https://github.com/ZhuoxuanLi-CS/Mag-Mamba++
作者：Zhuoxuan Li (Tongji University); Tangwei Ye (Tongji University); Jieyuan Pei (Zhejiang University of Technology); Haina Liang (Tongji University); Lai Zhong Yuan (Shanghai Ballsnow Intelligent Technology Co., Ltd); Zihan Liu (Tongji University); Yiming Wu (Tongji University); Qi Zhang (Tongji University); Liang Hu (Tongji University)
关键词：POI推荐，Mamba磁拉普拉斯算子
17 G²PRO: Gradient-guided Graph Prompt Optimization for LLM-based POI Recommendation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818010++
作者：Nan Jiang (Nanyang Technological University); Haitao Yuan (Nanyang Technological University); Tianjun Wei (Nanyang Technological University); Yingpeng Du (Nanyang Technological University); Jianing Si (Beijing University of Posts and Telecommunications); Minxiao Chen (Beijing University of Posts and Telecommunications); Jie Zhang (Nanyang Technological University); Zhu Sun (Singapore University of Technology and Design)
关键词：POI推荐,LLM，RAG，知识图谱
18 Is the Last Check-In All You Need? Next POI Recommendation: Recall and Rerank
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817836++
代码 ：++https://github.com/XZJIsme/k1-poi++
作者：Zhengjia Xu (School of Computing, Macquarie University); Dingyang Lyu (School of Computing and Information Systems, University of Melbourne); Zitai Qiu (School of Computing, Macquarie University); Shan Xue (School of Computing, Macquarie University); Jian Yang (School of Computing, Macquarie University); Jia Wu (School of Computing, Macquarie University)
关键词：POI推荐，召回，重排
19 Towards Robust Travel Time Estimation: An Out-of-Distribution Generalization Approach
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817802++
代码 ：++https://github.com/CrazySpy/OOD4TTE_public++
作者：Xiwen Jiang (Renmin University of China); Chuan Zhou (Peking University); Xiaofeng Meng (Renmin University of China); Haoxuan Li (Peking University)
关键词：行程时间估计，分布外泛化，交通数据管理
20 FairTraj: Density-Aware Generative Data Augmentation for Fairness in Downstream Trajectory Learning Tasks
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817841++
代码 ：++https://github.com/witcozyT/FairTraj++
作者：Tao Wang (Zhejiang University); Yuanyuan Yao (Zhejiang University); Yian Wei (ccst, Zhejiang University); Junhao Zhu (Zhejiang University); Hamid Alinejad-Rokny (UNSW Sydney); Lu Chen (Zhejiang University)
关键词：公平性，轨迹，扩散模型，数据增强
21 REFINE: Trajectory Representation Learning via Closed-Loop Transcription
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817866++
代码 ：++https://github.com/Sean-Bin-Yang/REFINE++
作者：Sean Bin Yang (Aalborg University); Ying Sun (Chongqing University of Post and Telecommunications); Jilin Hu (East China Normal University); Zongyi Xu (Chongqing University of Post and Telecommunications); Kristian Torp (Aalborg University); Hua Lu (Aalborg University); Bin Yang (East China Normal University); Christian S. Jensen (Aalborg University)
关键词：轨迹表示学习，闭环转录
22 LATTE: Learning Adaptive Segmentation for Efficient and Effective Trajectory Similarity Learning
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817880++
代码 ：++https://github.com/jlliRUC/LATTE++
作者：Jialiang Li (Roskilde University); Hua Lu (Aalborg University); Tiantian Liu (Aalborg University); Zhichen Lai (Fuzhou University); Pengfei Li (Roskilde University)
关键词：轨迹相似度学习，自适应轨迹分割
23 Road-Constrained Vehicle Trajectory Recovery from Traffic Video Using Spatio-Temporal Voxel Representation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817633++
代码 ：++https://github.com/taihangd/RETRIEVE++
作者：Taihang Dong (The State Key Laboratory of Blockchain and Data Security, Zhejiang University); Jun Zhang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University); Ping Chen (The State Key Laboratory of Blockchain and Data Security, Zhejiang University,Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security); Rongkai Wang (School of Electrical Engineering and Automation, Fuzhou University); Yu Fu (School of Information Science and Engineering, Lanzhou University); Dingyu Yang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University)
关键词：车辆轨迹恢复，时空建模，交通视频分析
24 On Optimizing Route-Responsive Urban Tree Placement in City-Scale Pedestrian Networks
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817687++
代码 ：++https://github.com/TianyouG/RUTO++
作者：Tianyou Gao (Kyoto University); Takayuki Ito (Kyoto University)
关键词：城市树木选址，空间决策支持，决策依赖型优化，近似算法
25 UNITE: A Unified Framework for Accurate and Efficient Origin-Destination and Route Travel Time Estimation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818012++
代码 ：++https://github.com/derekwtian/UNITE++
作者：Wei Tian (Hong Kong Polytechnic University); Jieming Shi (Hong Kong Polytechnic University); Man Lung Yiu (Hong Kong Polytechnic University)
关键词：行程时间估计，时空建模，路网
Applied Data Science
26 DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818375++
作者：Yanming Lyu (Beijing Jiaotong University); Yue Cheng (Beijing Jiaotong University); Lingkun Li (Beijing Jiaotong University); Ruipeng Gao (Beijing Jiaotong University); Xinyue Liu (Didichuxing Co. Ltd); Hui Gao (Didichuxing Co. Ltd); Qiang Ni (Lancaster University)
关键词：行程时间估计，交通预测，持续学习
27 A Data-driven Route Segmentation Framework for Time-of-Arrival Estimation Service
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818309++
作者：Jiangyi Fang (Key Lab of High Confidence Software Technologies, Peking University,School of Computer Science, Peking University); Liyue Chen (ByteDance Inc.); Yinfeng Xiang (Zhejiang University); Xi Sun (MetaLight HK Limited); Hui Zhong (MetaLight HK Limited); Leye Wang (Key Lab of High Confidence Software Technologies, Peking University,School of Computer Science, Peking University)
关键词：行程时间估计，轨迹挖掘，路线划分
AI for Sciences
28 Hybrid Graph Learning Reconstructs Global Ocean Oxygen Spatiotemporal Changes
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818938++
作者：Bin Lu (School of Information Science and Electronic Engineering, Shanghai Jiao Tong University); Luyu Han (Department of Computer Science and Engineering, University of California, San Diego); Ze Zhao (School of Information Science and Electronic Engineering, Shanghai Jiao Tong University); Jingjing Shen (School of Oceanography, Shanghai Jiao Tong University); Haonan Qi (School of Information Science and Electronic Engineering, Shanghai Jiao Tong University); Xiaoying Gan (School of Information Science and Electronic Engineering, Shanghai Jiao Tong University); Lei Zhou (School of Oceanography, Shanghai Jiao Tong University); Meng Jin (School of Artificial Intelligence, Shanghai Jiao Tong University); Lixin Qu (School of Oceanography, Shanghai Jiao Tong University); Yuntao Zhou (School of Oceanography, Shanghai Jiao Tong University); Luoyi Fu (School of Computer Science, Shanghai Jiao Tong University); Xinbing Wang (School of Information Science and Electronic Engineering, Shanghai Jiao Tong University); Chenghu Zhou (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences); Jing Zhang (State Key Laboratory of Estuarine and Coastal Research, East China Normal University)
关键词：人工智能在气候变化中的应用，图神经网络，时空数据挖掘，海洋脱氧
29 Collaborative Deterministic-Probabilistic Learning for Real-World Spatiotemporal Dynamics
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818828++
代码 ：++https://github.com/tsinghua-fib-lab/CoST++
作者：Zhi Sheng (Department of Electronic Engineering, Tsinghua University,Beijing National Research Center for Information Science and Technology, Tsinghua University); Yuan Yuan (Courant Institute of Mathematical Sciences, New York University); Yudi Zhang (School of Architecture, Tsinghua University); Jingtao Ding (Department of Electronic Engineering, Tsinghua University,Beijing National Research Center for Information Science and Technology, Tsinghua University); Yong Li (Department of Electronic Engineering, Tsinghua University,Beijing National Research Center for Information Science and Technology, Tsinghua University)
关键词：时空预测，扩散模型，不确定性量化，概率预测，科学机器学习
30 MUSTANG: Multi-Variable Spatio-Temporal Meta-Learning for Water Data Imputation
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818947++
代码 ：++https://github.com/Coropt/MUSTANG++
作者：Yaotian Zhu (Northwestern University); Ruiyao Xu (Northwestern University); Zhaoyang Guan (Northwestern University); Kexin Zhang (Northwestern University); Noah Rudko (San Francisco Estuary Institute,University of Arkansas - Fayetteville); Chuxu Zhang (University of Connecticut); Rebecca L. Muenich (University of Arkansas - Fayetteville); K. Selcuk Candan (Arizona State University); Kaize Ding (Northwestern University)
关键词：数据插补，迁移学习，水文系统
31 UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3819055++
代码 ：++https://github.com/Onedean/UrbanFM++
作者：Wei Chen (INTR & DSA Thrust, The Hong Kong University of Science and Technology (Guangzhou),CSE Department, The Hong Kong University of Science and Technology); Yuqian Wu (DSA Thrust, The Hong Kong University of Science and Technology (Guangzhou)); Junle Chen (CSE Department, The Hong Kong University of Science and Technology); Xiaofang Zhou (CSE Department, Hong Kong University of Science and Technology); Yuxuan Liang (INTR & DSA Thrust, The Hong Kong University of Science and Technology (Guangzhou))
关键词：城市移动科学，基础模型，时空数据
32 Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3818889++
作者：Wen Ye (University of Southern California); Muyan Weng (University of Southern California); Chuizheng Meng (University of Southern California); Hao Niu (KDDI Research, Inc.); Yizhou Zhang (University of Southern California); Yan Liu (University of Southern California)
关键词：时空系统，合成数据生成，人类移动性，扩散模型
Datasets and Benchmarks
33 UrbanWell: Benchmarking Multimodal Large Language Models for Spatio-Temporal Urban Wellbeing Analytics
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817584++
代码 ：++https://github.com/axin1301/UrbanWell-Benchmark++
作者：Yanxin Xi (Department of Computer Science, University of Helsinki); Xiang Su (Department of Computer Science, Department of Agricultural Sciences, University of Helsinki); Jie Feng (Zhongguancun Academy); Yu Liu (Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford); Sasu Tarkoma (Department of Computer Science, University of Helsinki); Pan Hui (Computational Media and Arts Thrust, Hong Kong University of Science and Technology (Guangzhou),Department of Computer Science, University of Helsinki)
关键词：城市福祉，多模态大型语言模型，时空分析，基准测试
34 AgentCity: An AI-Maintained Continuous Benchmark for Traffic Prediction
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817547++
代码 ：++https://github.com/Beihang-BIGSCity/AgentCity++
作者：Dayan Pan (School of Computer Science and Engineering, Beihang University,MOE Engineering Research Center of Advanced Computer Application Technology, Beihang University); Hongkang Su (School of Computer Science and Engineering, Beihang University, Beijing,MOE Engineering Research Center of Advanced Computer Application Technology, Beihang University); Jingyuan Wang (School of Computer Science and Engineering, Beihang University,School of Economics and Management, Beihang University); Xie Yu (School of Computer Science and Engineering, Beihang University,MOE Engineering Research Center of Advanced Computer Application Technology, Beihang University)
关键词：交通预测，benchmark，多智能体
35 MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios
链接 ：++https://dl.acm.org/doi/10.1145/3770855.3817498++
代码 ：++https://github.com/AMAP-ML/MobilityBench++
作者：Zhiheng Song (Computer Network Information Center, Chinese Academy of Sciences,University of Chinese Academy of Sciences); Jingshuai Zhang (AMAP, Alibaba Group); Chuan Qin (Computer Network Information Center, Chinese Academy of Sciences,University of Chinese Academy of Sciences); Chao Wang (Independent Researcher); Chao Chen (AMAP, Alibaba Group); Longfei Xu (AMAP, Alibaba Group); Kaikui Liu (AMAP, Alibaba Group); Xiangxiang Chu (AMAP, Alibaba Group); Hengshu Zhu (Computer Network Information Center, Chinese Academy of Sciences,University of Chinese Academy of Sciences)
关键词：LLM，路线规划智能体，benchmark
