mlsanityData to 14 Oct 2026

GeBDA: Building Damage Assessment as Text-Based Sequence Prediction

arXiv 2608.28567 ↗First posted 28 Aug 2026cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Conventionally, Building Damage Assessment (BDA) is tackled either with dedicated network architectures or by fine-tuning geospatial image foundation models. In this work, we ask whether a general-purpose Vision-Language Model (VLM) can localize buildings and grade their damage through autoregressive sequence generation alone. We cast BDA as predicting a variable-length set of bounding boxes, each specified by its coordinates and a damage label. Our preliminary implementation, based on the open Gemma model, achieves promising damage mapping results from only bi-temporal satellite images and a suitable text prompt.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 36 references that are in the map. First posted on arXiv 28 Aug 2026.

Builds on

26 of 36 references.

References · 26

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2025SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Featurescited by 1,188
  5. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 905
  6. 2023LISA: Reasoning Segmentation via Large Language Modelcited by 776
  7. 2021Pix2seq: A Language Modeling Framework for Object Detectioncited by 349
  8. 2023GeoChat: Grounded Large Vision-Language Model for Remote Sensingcited by 328
  9. 2024PaliGemma 2: A Family of Versatile VLMs for Transfercited by 207
  10. 2024EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domaincited by 184
  11. 2019xBD: A Dataset for Assessing Building Damage from Satellite Imagerycited by 139
  12. 2024ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Modelcited by 120
14 more
  1. 2024SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Modelcited by 113
  2. 2024PSALM: Pixelwise SegmentAtion with Large Multi-Modal Modelcited by 101
  3. 2024EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialoguescited by 85
  4. 2025Detect Anything via Next Point Predictioncited by 73
  5. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Datacited by 70
  6. 2024GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Taskscited by 51
  7. 2025BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster responsecited by 41
  8. 2025DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Responsecited by 36
  9. 2024CHOICE: Benchmarking the Remote Sensing Capabilities of Large Vision-Language Modelscited by 22
  10. 2025Object Detection with Multimodal Large Vision-Language Models: An In-depth Reviewcited by 14
  11. 2024RescueADI: Adaptive Disaster Interpretation in Remote Sensing Images with Autonomous Agentscited by 11
  12. 2025SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Imagescited by 10
  13. 2026DisasterInsight: A Building-Centric Benchmark for Evaluating Vision--Language Models in Disaster Responsecited by 2
  14. 2026From Pixels to Semantics: A Multi-Stage AI Framework for Structural Damage Detection in Satellite Imagerycited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2023Learning Efficient Unsupervised Satellite Image-based Building Damage Detection
  2. 2026DamageScope: Vision-Language Retrieval at Scale for Disaster Damage Assessment from Satellite Imagery
  3. 2025Effective Damage Data Generation by Fusing Imagery with Human Knowledge Using Vision-Language Models
  4. 2026Keep Your Friends Close, and the Right Neighbours Closer: Disaster-Conditioned Kernel-Regularized Graph Attention for Building Damage Classification
  5. 2026Assessing the Benefits of Combining Advanced Deep Learning Techniques for Post-Disaster Building Damage Assessment from UAV Imagery
  6. 2025SDIGLM: Leveraging Large Language Models and Multi-Modal Chain of Thought for Structural Damage Identification
  7. 2026Quantized Vision-Language Models for Damage Assessment: A Comparative Study of LLaVA-1.5-7B Quantization Levels
  8. 2024Towards Zero-Shot Annotation of the Built Environment with Vision-Language Models (Vision Paper)