mlsanityData to 14 Oct 2026

TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data

arXiv 2410.06234 ↗First posted 8 Oct 2024cs.CV cs.AI cs.LGcited by 70

Not on the map. Why?

Cited by 30 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large vision and language assistants have enabled new capabilities for interpreting natural images. These approaches have recently been adapted to earth observation data, but they are only able to handle single image inputs, limiting their use for many real-world tasks. In this work, we develop a new vision and language assistant called TEOChat that can engage in conversations about temporal sequences of earth observation data. To train TEOChat, we curate an instruction-following dataset composed of many single image and temporal tasks including building change and damage assessment, semantic change detection, and temporal scene classification. We show that TEOChat can perform a wide variety of spatial and temporal reasoning tasks, substantially outperforming previous vision and language assistants, and even achieving comparable or better performance than several specialist models trained to perform specific tasks. Furthermore, TEOChat achieves impressive zero-shot performance on a change detection and change question answering dataset, outperforms GPT-4o and Gemini 1.5 Pro on multiple temporal tasks, and exhibits stronger single image capabilities than a comparable single image instruction-following model on scene classification, visual question answering, and captioning. We publicly release our data, model, and code at https://github.com/ermongroup/TEOChat .

Key facts. Cited by 70 papers in the map (data through 14 Oct 2026). Builds on 66 of its 103 references that are in the map. First posted on arXiv 8 Oct 2024.

Builds on

66 of 103 references.

References · 66

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38 more
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50 most cited of 66 All 66 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 35; 2026: 33.

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  1. 2025ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Taskscited by 46
  2. 2025A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontierscited by 37
  3. 2025DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Responsecited by 36
  4. 2024Remote Sensing SpatioTemporal Vision-Language Models: A Comprehensive Surveycited by 23
  5. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectivescited by 18
  6. 2025DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understandingcited by 18
  7. 2025GeoVLM-R1: Reinforcement Fine-Tuning for Improved Remote Sensing Reasoningcited by 15
  8. 2026OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agentscited by 15
  9. 2025RSCC: A Large-Scale Remote Sensing Change Caption Dataset for Disaster Eventscited by 14
  10. 2025GeoZero: Incentivizing Reasoning from Scratch on Geospatial Scenescited by 14
  11. 2025LISAT: Language-Instructed Segmentation Assistant for Satellite Imagerycited by 13
  12. 2026Foundation Models in Remote Sensing: Evolving from Unimodality to Multimodalitycited by 12
38 more
  1. 2025Quality-Driven Curation of Remote Sensing Vision-Language Data via Learned Scoring Modelscited by 11
  2. 2025GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensingcited by 10
  3. 2025SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Imagescited by 10
  4. 2024UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language Modelscited by 9
  5. 2025Robust Change Captioning in Remote Sensing: SECOND-CC Dataset and MModalCC Frameworkcited by 8
  6. 2025InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognitioncited by 8
  7. 2026RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMscited by 8
  8. 2025BTCChat: Advancing Remote Sensing Bi-temporal Change Captioning with Multimodal Large Language Modelcited by 7
  9. 2026TerraScope: Pixel-Grounded Visual Reasoning for Earth Observationcited by 7
  10. 2025FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mappingcited by 6
  11. 2026GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensingcited by 6
  12. 2025DescribeEarth: Describe Anything for Remote Sensing Imagescited by 5
  13. 2026Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Taskscited by 4
  14. 2025Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localizationcited by 3
  15. 2025Domain Specific Benchmarks for Evaluating Multimodal Large Language Modelscited by 3
  16. 2025GeoProg3D: Compositional Visual Reasoning for City-Scale 3D Language Fieldscited by 3
  17. 2025Co-Training Vision Language Models for Remote Sensing Multi-task Learningcited by 3
  18. 2025ViLaCD-R1: A Vision-Language Framework for Semantic Change Detection in Remote Sensingcited by 3
  19. 2025TAMMs: Change Understanding and Forecasting in Satellite Image Time Series with Temporal-Aware Multimodal Modelscited by 2
  20. 2025Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modelingcited by 2
  21. 2025MONITRS: Multimodal Observations of Natural Incidents Through Remote Sensingcited by 2
  22. 2025ChatENV: An Interactive Vision-Language Model for Sensor-Guided Environmental Monitoring and Scenario Simulationcited by 2
  23. 2026DisasterInsight: A Building-Centric Benchmark for Evaluating Vision--Language Models in Disaster Responsecited by 2
  24. 2026RS-WorldModel: a Unified Model for Remote Sensing Understanding and Future Sense Forecastingcited by 2
  25. 2026BigEarthNet.txt: A Large-Scale Multi-Sensor Image-Text Dataset and Benchmark for Earth Observationcited by 2
  26. 2026RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observationcited by 2
  27. 2026Agentic AI for Remote Sensing: Technical Challenges and Research Directionscited by 2
  28. 2026RSICCLLM: A Multimodal Large Language Model for Remote Sensing Image Change Captioningcited by 2
  29. 2026RingMoClaw: An Experience-Inspired Multi-Agent Framework for Self-Evolving Research in Remote Sensingcited by 2
  30. 2025Remote Sensing Image Intelligent Interpretation with the Language-Centered Perspective: Principles, Methods and Challengescited by 1
  31. 2025The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2cited by 1
  32. 2025Think First, Assign Next (ThiFAN-VQA): A Two-stage Chain-of-Thought Framework for Post-Disaster Damage Assessmentcited by 1
  33. 2025Geo3DVQA: Evaluating Vision-Language Models for 3D Geospatial Reasoning from Aerial Imagerycited by 1
  34. 2026Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Modelscited by 1
  35. 2025Operational Change Detection for Geographical Information: Overview and Challengescited by 0
  36. 2025Multilingual Training-Free Remote Sensing Image Captioningcited by 0
  37. 2025SATGround: A Spatially-Aware Approach for Visual Grounding in Remote Sensingcited by 0
  38. 2025VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensingcited by 0

50 most cited of 70 All 70 (JSON)

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  1. 2026LongEarth-R1: Benchmarking and Aligning Vision-Language Models for Long-Horizon Earth Observation Reasoning
  2. 2024EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues
  3. 2025GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing
  4. 2025DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation
  5. 2026OmniEarth: A Benchmark for Evaluating Vision-Language Models in Geospatial Tasks
  6. 2024Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data
  7. 2024ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuning
  8. 2026Selective Tool Use for Agentic Change Visual Question Answering in Remote Sensing