mlsanityData to 14 Oct 2026

Integration of Large Vision Language Models for Efficient Post-disaster Damage Assessment and Reporting

arXiv 2411.01511 ↗First posted 3 Nov 2024cs.MA cs.CLcited by 6

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

Abstract (arXiv)

Traditional natural disaster response involves significant coordinated teamwork where speed and efficiency are key. Nonetheless, human limitations can delay critical actions and inadvertently increase human and economic losses. Agentic Large Vision Language Models (LVLMs) offer a new avenue to address this challenge, with the potential for substantial socio-economic impact, particularly by improving resilience and resource access in underdeveloped regions. We introduce DisasTeller, the first multi-LVLM-powered framework designed to automate tasks in post-disaster management, including on-site assessment, emergency alerts, resource allocation, and recovery planning. By coordinating four specialised LVLM agents with GPT-4 as the core model, DisasTeller autonomously implements disaster response activities, reducing human execution time and optimising resource distribution. Our evaluations through both LVLMs and humans demonstrate DisasTeller's effectiveness in streamlining disaster response. This framework not only supports expert teams but also simplifies access to disaster management processes for non-experts, bridging the gap between traditional response methods and LVLM-driven efficiency.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 13 of its 44 references that are in the map. First posted on arXiv 3 Nov 2024.

Builds on

13 of 44 references.

References · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  5. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  6. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
  7. 2022Scaling Laws for Reward Model Overoptimizationcited by 1,095
  8. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
  9. 2022A Survey on In-context Learningcited by 721
  10. 2023ChemCrow: Augmenting large-language models with chemistry toolscited by 631
  11. 2023How is ChatGPT's behavior changing over time?cited by 270
  12. 2023Factuality Challenges in the Era of Large Language Modelscited by 126
1 more
  1. 2024EVEDIT: Event-based Knowledge Editing with Deductive Editing Boundariescited by 16

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.

  1. 2025CyPortQA: Benchmarking Multimodal Large Language Models for Cyclone Preparedness in Port Operationcited by 3
  2. 2026EgoPolice: A Benchmark for Egocentric Video Understanding in High-Stakes Police Body-Worn Camera Footagecited by 2
  3. 2026Risk-Conditioned Fine-Tuning of Large Language Modelscited by 1
  4. 2026Ground-Truth Depth in Vision Language Models: Spatial Context Understanding in Conversational AI for XR-Robotic Support in Emergency First Responsecited by 0
  5. 2026LandslideAgent with Multimodal LandslideBench: A Domain-Rule-Augmented Agent for Autonomous Landslide Identification and Analysiscited by 0
  6. 2026RAPIDMap: Rapid Multi-Agent Pipeline for Interpretable Disaster Mapping from Satellite and Street-view Imagerycited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations
  2. 2025Disaster Management in the Era of Agentic AI Systems: A Vision for Collective Human-Machine Intelligence for Augmented Resilience
  3. 2026GeoDisaster: Benchmarking Orchestrated Agents for Operational Disaster Geo-Intelligence
  4. 2026A Systems Engineering Framework for Vision-Language-Enabled UAV Triage and Disaster Response
  5. 2026DisasterInsight: A Building-Centric Benchmark for Evaluating Vision--Language Models in Disaster Response
  6. 2026Instruct-ICL: Instruction-Guided In-Context Learning for Post-Disaster Damage Assessment
  7. 2025Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response
  8. 2025A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation