{"total":308,"rows":[{"id":"2306.11029","title":"RemoteCLIP: A Vision Language Foundation Model for Remote Sensing","created":"2023-06-19","cited_by_count":363,"area":"mllm"},{"id":"2301.10343","title":"ClimaX: A foundation model for weather and climate","created":"2023-01-24","cited_by_count":337,"area":null},{"id":"2312.10115","title":"SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery","created":"2023-12-15","cited_by_count":205,"area":null},{"id":"2401.16822","title":"EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domain","created":"2024-01-30","cited_by_count":184,"area":"mllm"},{"id":"2306.16269","title":"RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model","created":"2023-06-28","cited_by_count":181,"area":null},{"id":"2311.00566","title":"CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders","created":"2023-11-01","cited_by_count":169,"area":null},{"id":"2412.02732","title":"Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications","created":"2024-12-03","cited_by_count":144,"area":null},{"id":"2402.02544","title":"LHRS-Bot: Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Model","created":"2024-02-04","cited_by_count":138,"area":"mllm"},{"id":"2312.12856","title":"SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing","created":"2023-12-20","cited_by_count":125,"area":"mllm"},{"id":"2403.15356","title":"Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation","created":"2024-03-22","cited_by_count":104,"area":null},{"id":"2304.14065","title":"Lightweight, Pre-trained Transformers for Remote Sensing Timeseries","created":"2023-04-27","cited_by_count":103,"area":null},{"id":"2403.05419","title":"Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery","created":"2024-03-08","cited_by_count":83,"area":null},{"id":"2402.01444","title":"Mission Critical -- Satellite Data is a Distinct Modality in Machine Learning","created":"2024-02-02","cited_by_count":77,"area":null},{"id":"2405.02771","title":"MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning","created":"2024-05-04","cited_by_count":77,"area":null},{"id":"2412.14123","title":"AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities","created":"2024-12-18","cited_by_count":74,"area":null},{"id":"2406.11519","title":"HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model","created":"2024-06-17","cited_by_count":73,"area":null},{"id":"2412.04204","title":"PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models","created":"2024-12-05","cited_by_count":68,"area":null},{"id":"2403.13430","title":"MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining","created":"2024-03-20","cited_by_count":66,"area":null},{"id":"2404.08351","title":"OmniSat: Self-Supervised Modality Fusion for Earth Observation","created":"2024-04-12","cited_by_count":63,"area":null},{"id":"2304.05215","title":"A Billion-scale Foundation Model for Remote Sensing Images","created":"2023-04-11","cited_by_count":62,"area":null},{"id":"2304.07213","title":"Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar","created":"2023-04-14","cited_by_count":60,"area":null},{"id":"2503.11849","title":"Towards a Unified Copernicus Foundation Model for Earth Vision","created":"2025-03-14","cited_by_count":53,"area":null},{"id":"2408.09110","title":"Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community","created":"2024-08-17","cited_by_count":50,"area":null},{"id":"2306.09424","title":"SSL4EO-L: Datasets and Foundation Models for Landsat Imagery","created":"2023-06-15","cited_by_count":49,"area":null},{"id":"2310.18653","title":"Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing","created":"2023-10-28","cited_by_count":48,"area":null},{"id":"2401.15855","title":"Cross-Scale MAE: A Tale of Multi-Scale Exploitation in Remote Sensing","created":"2024-01-29","cited_by_count":47,"area":null},{"id":"2311.15153","title":"Predicting Gradient is Better: Exploring Self-Supervised Learning for SAR ATR with a Joint-Embedding Predictive Architecture","created":"2023-11-26","cited_by_count":46,"area":null},{"id":"2502.09356","title":"Galileo: Learning Global & Local Features of Many Remote Sensing Modalities","created":"2025-02-13","cited_by_count":43,"area":null},{"id":"2405.13570","title":"MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation","created":"2024-05-22","cited_by_count":42,"area":null},{"id":"2408.08447","title":"SpectralEarth: Training Hyperspectral Foundation Models at Scale","created":"2024-08-15","cited_by_count":42,"area":null},{"id":"2505.18022","title":"RemoteSAM: Towards Segment Anything for Earth Observation","created":"2025-05-23","cited_by_count":39,"area":null},{"id":"2506.20380","title":"TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis","created":"2025-06-25","cited_by_count":39,"area":null},{"id":"2401.02013","title":"SwitchTab: Switched Autoencoders Are Effective Tabular Learners","created":"2024-01-04","cited_by_count":38,"area":null},{"id":"2406.17998","title":"Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model","created":"2024-06-26","cited_by_count":37,"area":null},{"id":"2411.00683","title":"TaxaBind: A Unified Embedding Space for Ecological Applications","created":"2024-11-01","cited_by_count":35,"area":null},{"id":"2503.10845","title":"Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation","created":"2025-03-13","cited_by_count":34,"area":null},{"id":"2402.19348","title":"Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook","created":"2024-02-29","cited_by_count":33,"area":null},{"id":"2405.04285","title":"On the Foundations of Earth and Climate Foundation Models","created":"2024-05-07","cited_by_count":33,"area":null},{"id":"2404.06637","title":"GeoSynth: Contextually-Aware High-Resolution Satellite Image Synthesis","created":"2024-04-09","cited_by_count":32,"area":null},{"id":"2312.10114","title":"FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring","created":"2023-12-15","cited_by_count":31,"area":null},{"id":"2408.06687","title":"Masked Image Modeling: A Survey","created":"2024-08-13","cited_by_count":29,"area":null},{"id":"2312.02199","title":"USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery","created":"2023-12-02","cited_by_count":28,"area":null},{"id":"2405.20462","title":"Multi-Label Guided Soft Contrastive Learning for Efficient Earth Observation Pretraining","created":"2024-05-30","cited_by_count":28,"area":null},{"id":"2305.13456","title":"Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters","created":"2023-05-22","cited_by_count":27,"area":null},{"id":"2410.22629","title":"CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic Segmentation","created":"2024-10-30","cited_by_count":27,"area":null},{"id":"2507.13812","title":"SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing","created":"2025-07-18","cited_by_count":26,"area":null},{"id":"2310.18541","title":"ReConTab: Regularized Contrastive Representation Learning for Tabular Data","created":"2023-10-28","cited_by_count":25,"area":null},{"id":"2401.04464","title":"PhilEO Bench: Evaluating Geo-Spatial Foundation Models","created":"2024-01-09","cited_by_count":25,"area":null},{"id":"2405.09365","title":"SARATR-X: Toward Building A Foundation Model for SAR Target Recognition","created":"2024-05-15","cited_by_count":25,"area":null},{"id":"2503.20563","title":"TerraTorch: The Geospatial Foundation Models Toolkit","created":"2025-03-26","cited_by_count":25,"area":null},{"id":"2506.06281","title":"TerraFM: A Scalable Foundation Model for Unified Multisensor Earth Observation","created":"2025-06-06","cited_by_count":25,"area":null},{"id":"2411.02796","title":"Specialized Foundation Models Struggle to Beat Supervised Baselines","created":"2024-11-05","cited_by_count":24,"area":null},{"id":"2503.23844","title":"FlexiMo: A Flexible Remote Sensing Foundation Model","created":"2025-03-31","cited_by_count":24,"area":null},{"id":"2511.13655","title":"OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observation","created":"2025-11-17","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":"2408.01946","title":"Masked Angle-Aware Autoencoder for Remote Sensing Images","created":"2024-08-04","cited_by_count":22,"area":null},{"id":"2506.17774","title":"PhysiX: A Foundation Model for Physics Simulations","created":"2025-06-21","cited_by_count":22,"area":null},{"id":"2306.08913","title":"Advancing Volumetric Medical Image Segmentation via Global-Local Masked Autoencoder","created":"2023-06-15","cited_by_count":21,"area":null},{"id":"2503.22081","title":"A Survey on Remote Sensing Foundation Models: From Vision to Multimodality","created":"2025-03-28","cited_by_count":19,"area":null},{"id":"2503.21841","title":"HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery","created":"2025-03-27","cited_by_count":17,"area":null},{"id":"2303.16198","title":"Multi-modal learning for geospatial vegetation forecasting","created":"2023-03-28","cited_by_count":16,"area":null},{"id":"2406.10973","title":"ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts","created":"2024-06-16","cited_by_count":16,"area":null},{"id":"2407.09392","title":"Open-Canopy: Towards Very High Resolution Forest Monitoring","created":"2024-07-12","cited_by_count":16,"area":null},{"id":"2504.03166","title":"RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretation","created":"2025-04-04","cited_by_count":16,"area":"moe"},{"id":"2311.00277","title":"OpenForest: A data catalogue for machine learning in forest monitoring","created":"2023-11-01","cited_by_count":15,"area":null},{"id":"2409.13366","title":"RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning","created":"2024-09-20","cited_by_count":15,"area":null},{"id":"2505.16793","title":"REOBench: Benchmarking Robustness of Earth Observation Foundation Models","created":"2025-05-22","cited_by_count":15,"area":"mllm"},{"id":"2309.07207","title":"EarthPT: a time series foundation model for Earth Observation","created":"2023-09-13","cited_by_count":14,"area":null},{"id":"2309.10667","title":"Learning Tri-modal Embeddings for Zero-Shot Soundscape Mapping","created":"2023-09-19","cited_by_count":14,"area":null},{"id":"2401.00897","title":"Masked Modeling for Self-supervised Representation Learning on Vision and Beyond","created":"2023-12-31","cited_by_count":13,"area":null},{"id":"2310.19168","title":"BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping","created":"2023-10-29","cited_by_count":12,"area":null},{"id":"2401.07782","title":"Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing","created":"2024-01-15","cited_by_count":12,"area":null},{"id":"2406.11933","title":"Harnessing Massive Satellite Imagery with Efficient Masked Image Modeling","created":"2024-06-17","cited_by_count":12,"area":null},{"id":"2412.05600","title":"Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space","created":"2024-12-07","cited_by_count":12,"area":null},{"id":"2603.00988","title":"Foundation Models in Remote Sensing: Evolving from Unimodality to Multimodality","created":"2026-03-01","cited_by_count":12,"area":null},{"id":"2605.12678","title":"No One Knows the State of the Art in Geospatial Foundation Models","created":"2026-05-12","cited_by_count":12,"area":null},{"id":"2402.00407","title":"InfMAE: A Foundation Model in the Infrared Modality","created":"2024-02-01","cited_by_count":11,"area":null},{"id":"2406.08079","title":"A$^{2}$-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder","created":"2024-06-12","cited_by_count":11,"area":null},{"id":"2407.11696","title":"Global atmospheric data assimilation with multi-modal masked autoencoders","created":"2024-07-16","cited_by_count":11,"area":null},{"id":"2410.19965","title":"OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery","created":"2024-10-25","cited_by_count":11,"area":null},{"id":"2411.17984","title":"RS-vHeat: Heat Conduction Guided Efficient Remote Sensing Foundation Model","created":"2024-11-27","cited_by_count":11,"area":null},{"id":"2412.19237","title":"SeaMo: A Season-Aware Multimodal Foundation Model for Remote Sensing","created":"2024-12-26","cited_by_count":11,"area":null},{"id":"2501.08111","title":"EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision","created":"2025-01-14","cited_by_count":11,"area":null},{"id":"2503.10392","title":"RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing","created":"2025-03-13","cited_by_count":11,"area":"ssm"},{"id":"2503.07890","title":"Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?","created":"2025-03-10","cited_by_count":10,"area":"diffusion"},{"id":"2503.09493","title":"Parameter-Efficient Adaptation of Geospatial Foundation Models through Embedding Deflection","created":"2025-03-12","cited_by_count":10,"area":null},{"id":"2503.16683","title":"GAIR: Location-Aware Self-Supervised Contrastive Pre-Training with Geo-Aligned Implicit Representations","created":"2025-03-20","cited_by_count":10,"area":null},{"id":"2505.24528","title":"Geospatial Foundation Models to Enable Progress on Sustainable Development Goals","created":"2025-05-30","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":"2511.02101","title":"Measuring the Intrinsic Dimension of Earth Representations","created":"2025-11-03","cited_by_count":10,"area":null},{"id":"2310.00022","title":"CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding","created":"2023-09-28","cited_by_count":9,"area":null},{"id":"2407.14651","title":"Improving Representation of High-frequency Components for Medical Visual Foundation Models","created":"2024-07-19","cited_by_count":9,"area":null},{"id":"2505.21357","title":"AgriFM: A Multi-source Temporal Remote Sensing Foundation Model for Agriculture Mapping","created":"2025-05-27","cited_by_count":9,"area":null},{"id":"2506.19585","title":"SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing Images","created":"2025-06-24","cited_by_count":9,"area":null},{"id":"2509.17562","title":"Visual Instruction Pretraining for Domain-Specific Foundation Models","created":"2025-09-22","cited_by_count":9,"area":null},{"id":"2601.00857","title":"Harvesting AlphaEarth: Benchmarking the Geospatial Foundation Model for Agricultural Downstream Tasks","created":"2025-12-30","cited_by_count":9,"area":null},{"id":"2311.08863","title":"Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques","created":"2023-11-15","cited_by_count":8,"area":null},{"id":"2401.00463","title":"Analyzing Local Representations of Self-supervised Vision Transformers","created":"2023-12-31","cited_by_count":8,"area":null},{"id":"2403.01915","title":"xT: Nested Tokenization for Larger Context in Large Images","created":"2024-03-04","cited_by_count":8,"area":null},{"id":"2406.18295","title":"Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AI","created":"2024-06-26","cited_by_count":8,"area":null}],"next_cursor":"100"}