{"total":17,"rows":[{"id":"2408.10269","title":"OpenCity: Open Spatio-Temporal Foundation Models for Traffic Prediction","created":"2024-08-16","cited_by_count":27,"area":null},{"id":"2412.00953","title":"BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis","created":"2024-12-01","cited_by_count":16,"area":null},{"id":"2411.18428","title":"MM-Path: Multi-modal, Multi-granularity Path Representation Learning -- Extended Version","created":"2024-11-27","cited_by_count":14,"area":null},{"id":"2410.12593","title":"Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting","created":"2024-10-16","cited_by_count":10,"area":null},{"id":"2506.01364","title":"Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review","created":"2025-06-02","cited_by_count":10,"area":null},{"id":"2506.00635","title":"Learning with Calibration: Exploring Test-Time Computing of Spatio-Temporal Forecasting","created":"2025-05-31","cited_by_count":9,"area":null},{"id":"2410.20856","title":"Strada-LLM: Graph LLM for traffic prediction","created":"2024-10-28","cited_by_count":3,"area":null},{"id":"2504.02009","title":"Urban Computing in the Era of Large Language Models","created":"2025-04-02","cited_by_count":2,"area":null},{"id":"2509.10528","title":"STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions","created":"2025-09-04","cited_by_count":2,"area":null},{"id":"2602.10502","title":"Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Web","created":"2026-02-11","cited_by_count":2,"area":null},{"id":"2411.15893","title":"Distribution-aware Online Continual Learning for Urban Spatio-Temporal Forecasting","created":"2024-11-24","cited_by_count":1,"area":null},{"id":"2504.13961","title":"CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee","created":"2025-04-17","cited_by_count":0,"area":null},{"id":"2505.05155","title":"FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2605.18793","title":"Dimensional Balance Improves Large Scale Spatiotemporal Prediction Performance","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2606.08303","title":"GeoGNN: Time Series Geo-Localization using Two-Tower Graph Neural Networks","created":"2026-06-06","cited_by_count":0,"area":null},{"id":"2606.13119","title":"MP3: Multi-Period Pattern Pre-training for Spatio-Temporal Forecasting","created":"2026-06-11","cited_by_count":0,"area":null},{"id":"2606.15642","title":"CIWI-CKT: Chaos-Informed Wave Interference Feature Fusion and Cross-City Knowledge Transfer for Traffic Flow Forecasting","created":"2026-06-14","cited_by_count":0,"area":null}],"next_cursor":null}