mlsanityData to 7 Oct 2026

FUSE-RSVLM: Feature Fusion Vision-Language Model for Remote Sensing

arXiv 2512.24022 ↗First posted 30 Dec 2025cs.CV cs.AIcited by 3

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

Large vision-language models (VLMs) exhibit strong performance across various tasks. However, these VLMs encounter significant challenges when applied to the remote sensing domain due to the inherent differences between remote sensing images and natural images. Existing remote sensing VLMs often fail to extract fine-grained visual features and suffer from visual forgetting during deep language processing. To address this, we introduce MF-RSVLM, a Multi-Feature Fusion Remote Sensing Vision--Language Model that effectively extracts and fuses visual features for RS understanding. MF-RSVLM learns multi-scale visual representations and combines global context with local details, improving the capture of small and complex structures in RS scenes. A recurrent visual feature injection scheme ensures the language model remains grounded in visual evidence and reduces visual forgetting during generation. Extensive experiments on diverse RS benchmarks show that MF-RSVLM achieves state-of-the-art or highly competitive performance across remote sensing classification, image captioning, and VQA tasks. Our code is publicly available at https://github.com/Yunkaidang/RSVLM.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 49 of its 71 references that are in the map. First posted on arXiv 30 Dec 2025.

Builds on

49 of 71 references.

Closest ancestors · 15

Same direction, newest first

  1. 2025GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing8 Jul
  2. 2025GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution27 May
  3. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives20 May
  4. 2025When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning10 Mar
  5. 2025GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing23 Jan
  6. 2024EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues19 Dec
  7. 2024RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts7 Dec
  8. 2024GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding16 Nov
  9. 2024VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding18 Jun
  10. 2024SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding14 Jun
  11. 2024VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis29 Mar
  12. 2024LHRS-Bot: Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Model4 Feb
3 more
  1. 2024EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domain30 Jan
  2. 2023GeoChat: Grounded Large Vision-Language Model for Remote Sensing24 Nov
  3. 2023RSGPT: A Remote Sensing Vision Language Model and Benchmark28 Jul

Other references · 34

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,069
  3. 2025Qwen2.5-VL Technical Reportcited by 5,418
  4. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,310
  5. 2021Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervisioncited by 3,848
  6. 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuningcited by 2,855
  7. 2023InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Taskscited by 2,534
  8. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 2,179
  9. 2017EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classificationcited by 1,488
  10. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,419
  11. 2024MiniCPM-V: A GPT-4V Level MLLM on Your Phonecited by 1,061
  12. 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,033
22 more
  1. 2017Remote Sensing Image Scene Classification: Benchmark and State of the Artcited by 791
  2. 2017DOTA: A Large-scale Dataset for Object Detection in Aerial Imagescited by 622
  3. 2023MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningcited by 617
  4. 2023mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaborationcited by 545
  5. 2022SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagerycited by 402
  6. 2016AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classificationcited by 343
  7. 2019Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmarkcited by 339
  8. 2017Functional Map of the Worldcited by 338
  9. 2023InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Compositioncited by 297
  10. 2020RSVQA: Visual Question Answering for Remote Sensing Datacited by 197
  11. 2017Exploring Models and Data for Remote Sensing Image Caption Generationcited by 195
  12. 2023Multimodal Large Language Models: A Surveycited by 193
  13. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  14. 2022Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrievalcited by 77
  15. 2025FlexiMo: A Flexible Remote Sensing Foundation Modelcited by 24
  16. 2024SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detectioncited by 22
  17. 2022METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mappingcited by 17
  18. 2025HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagerycited by 16
  19. 2023RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question Answeringcited by 11
  20. 2023Exploring vision transformer layer choosing for semantic segmentationcited by 1
  21. 2025P2HCT: Plug-and-Play Hierarchical C2F Transformer for Multi-Scale Feature Fusioncited by 1
  22. 2025Unified Long Video Inpainting and Outpainting via Overlapping High-Order Co-Denoisingcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMscited by 7
  2. 2026UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensingcited by 1
  3. 2026CLASP: Class-Adaptive Layer Fusion and Dual-Stage Pruning for Multimodal Large Language Modelscited by 0

Similar, not cited

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  1. 2026Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?
  2. 2024Advancements in Visual Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
  3. 2025Co-Training Vision Language Models for Remote Sensing Multi-task Learning
  4. 2023RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensing
  5. 2025A Vision Centric Remote Sensing Benchmark
  6. 2025GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing
  7. 2023Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment
  8. 2025Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation