mlsanityData to 7 Oct 2026

Can Urban Blight Be Accessed with Vision-language Models: A Case Study in Detroit

arXiv 2608.01753 ↗First posted 3 Aug 2026cs.CV cs.AIcited by 0

On the map: Multimodal LLMs / vision-language models → Agricultural vision-language models

Abstract (arXiv)

Addressing urban blight has seen increased focus in the past 15 years. Assessing urban blight is essential for guiding urban planning, targeting rehabilitation, and safeguarding public health, yet traditional residential blight surveys are difficult to maintain at scale due to the labor-intensive cost and long-term cycle. This study introduced a scalable framework for estimating residential blight using open-source large vision-language models on multiple views. Structured prompts guided models to evaluate housing attributes, including roof integrity, wall damage, and broken or boarded openings, producing both binary assessments and probabilistic estimates of disrepair. To evaluate the performance of these visual assessments, we compared professional human annotations of these features across several models, including an ensemble stacking approach based on XGBoost and a weighted scoring system. Results showed that (i) multiple street views can contribute to the improvement of accuracy, (ii) large vision-language models have different strengths of inference, (iii) the ensemble learner outperforms individual base models, enhancing robustness across all residential conditions and blight assessment. The practical application of the method allows low-cost tracking and management of housing stock conditions, providing a regularly updatable complement to traditional blight surveys.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Agricultural vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 16 of its 60 references that are in the map. First posted on arXiv 3 Aug 2026.

Builds on

16 of 60 references.

References · 16

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2025Qwen2.5-VL Technical Reportcited by 5,418
  3. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  4. 2025Gemma 3 Technical Reportcited by 1,686
  5. 2025Harnessing Multiple Large Language Models: A Survey on LLM Ensemblecited by 86
  6. 2024UrbanGPT: Spatio-Temporal Large Language Modelscited by 81
  7. 2023UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Webcited by 77
  8. 2024OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agentscited by 35
  9. 2024CityGPT: Empowering Urban Spatial Cognition of Large Language Modelscited by 29
  10. 2024UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Modelscited by 13
  11. 2025OpenFACADES: An Open Framework for Architectural Caption and Attribute Data Enrichment via Street View Imagerycited by 8
  12. 2025A Simple Ensemble Strategy for LLM Inference: Towards More Stable Text Classificationcited by 8
4 more
  1. 2023Generative agents in the streets: Exploring the use of Large Language Models (LLMs) in collecting urban perceptionscited by 6
  2. 2024Evaluating and Enhancing Trustworthiness of LLMs in Perception Taskscited by 4
  3. 2025OpenCity3D: What do Vision-Language Models know about Urban Environments?cited by 3
  4. 2024Lessons from a human-in-the-loop machine learning approach for identifying vacant, abandoned, and deteriorated properties in Savannah, Georgiacited by 1

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  4. 2026Leveraging Multimodal LLMs for Built Environment and Housing Attribute Assessment from Street-View Imagery
  5. 2024Leveraging Vision Language Models for Specialized Agricultural Tasks
  6. 2024BuildingView: Constructing Urban Building Exteriors Databases with Street View Imagery and Multimodal Large Language Mode
  7. 2025Towards General Urban Monitoring with Vision-Language Models: A Review, Evaluation, and a Research Agenda
  8. 2024Harnessing Large Vision and Language Models in Agriculture: A Review