{"total":21,"rows":[{"id":"2406.15658","title":"TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning","created":"2024-06-21","cited_by_count":31,"area":null},{"id":"2503.13502","title":"Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2402.01749","title":"Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models","created":"2024-01-30","cited_by_count":23,"area":null},{"id":"2312.17016","title":"On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications","created":"2023-12-23","cited_by_count":15,"area":null},{"id":"2408.14806","title":"Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications","created":"2024-08-27","cited_by_count":13,"area":null},{"id":"2503.09128","title":"FlexiReg: Flexible Urban Region Representation Learning","created":"2025-03-12","cited_by_count":13,"area":null},{"id":"2403.09059","title":"LAMP: A Language Model on the Map","created":"2024-03-14","cited_by_count":9,"area":null},{"id":"2408.12133","title":"Self-Supervised Representation Learning for Geospatial Objects: A Survey","created":"2024-08-22","cited_by_count":9,"area":null},{"id":"2408.05920","title":"Urban Region Pre-training and Prompting: A Graph-based Approach","created":"2024-08-12","cited_by_count":8,"area":null},{"id":"2605.26036","title":"CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalities","created":"2026-05-25","cited_by_count":5,"area":null},{"id":"2504.16942","title":"S2Vec: Self-Supervised Geospatial Embeddings for the Built Environment","created":"2025-04-10","cited_by_count":4,"area":null},{"id":"2506.01297","title":"MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale","created":"2025-06-02","cited_by_count":4,"area":null},{"id":"2506.14570","title":"From Points to Places: Towards Human Mobility-Driven Spatiotemporal Foundation Models via Understanding Places","created":"2025-06-17","cited_by_count":3,"area":null},{"id":"2505.13526","title":"Geography-Aware Large Language Models for Next POI Recommendation","created":"2025-05-18","cited_by_count":2,"area":null},{"id":"2509.19354","title":"GeoResponder: Towards Building Geospatial LLMs for Time-Critical Disaster Response","created":"2025-09-18","cited_by_count":1,"area":null},{"id":"2602.15750","title":"UrbanVerse: Learning Urban Region Representation Across Cities and Tasks","created":"2026-02-17","cited_by_count":1,"area":null},{"id":"2606.02374","title":"Spatial Representation Learning Beyond Pixels: Unifying Raster Data and Vector Semantics for Human-Centric Geospatial Foundation Models","created":"2026-06-01","cited_by_count":1,"area":null},{"id":"2410.14281","title":"PLMTrajRec: A Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models","created":"2024-10-18","cited_by_count":0,"area":null},{"id":"2602.01610","title":"ToPT: Task-Oriented Prompt Tuning for Urban Region Representation Learning","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2605.12276","title":"NARA: Anchor-Conditioned Representation Learning for Heterogeneous Vector Geoentities","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2608.17848","title":"MoRAX: Mobility-based Representation Augmentation for Geospatial Foundation Models","created":"2026-08-18","cited_by_count":0,"area":null}],"next_cursor":null}