mlsanityData to 14 Oct 2026

DisasterResponseGPT: Large Language Models for Accelerated Plan of Action Development in Disaster Response Scenarios

arXiv 2306.17271 ↗First posted 29 Jun 2023cs.LGcited by 34

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Abstract (arXiv)

The development of plans of action in disaster response scenarios is a time-consuming process. Large Language Models (LLMs) offer a powerful solution to expedite this process through in-context learning. This study presents DisasterResponseGPT, an algorithm that leverages LLMs to generate valid plans of action quickly by incorporating disaster response and planning guidelines in the initial prompt. In DisasterResponseGPT, users input the scenario description and receive a plan of action as output. The proposed method generates multiple plans within seconds, which can be further refined following the user's feedback. Preliminary results indicate that the plans of action developed by DisasterResponseGPT are comparable to human-generated ones while offering greater ease of modification in real-time. This approach has the potential to revolutionize disaster response operations by enabling rapid updates and adjustments during the plan's execution.

Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). Builds on 10 of its 64 references that are in the map. First posted on arXiv 29 Jun 2023.

Builds on

10 of 64 references.

References · 10

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2022Training language models to follow instructions with human feedbackcited by 15,971
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  5. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  6. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,434
  7. 2023PaLM 2 Technical Reportcited by 1,162
  8. 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 938
  9. 2021How Many Data Points is a Prompt Worth?cited by 198
  10. 2022Graph Neural Network Enhanced Language Models for Efficient Multilingual Text Classificationcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 9; 2025: 18; 2026: 6.

34 papers.

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  1. 2025UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobilitycited by 49
  2. 2024Large Language Models for UAVs: Current State and Pathways to the Futurecited by 33
  3. 2025Multi-Agent Geospatial Copilots for Remote Sensing Workflowscited by 22
  4. 2025Harnessing Large Language Models for Disaster Management: A Surveycited by 20
  5. 2024From Text to Transformation: A Comprehensive Review of Large Language Models' Versatilitycited by 19
  6. 2024On Large Language Models in National Security Applicationscited by 19
  7. 2023Enhancing Emergency Decision-making with Knowledge Graphs and Large Language Modelscited by 12
  8. 2024COA-GPT: Generative Pre-trained Transformers for Accelerated Course of Action Development in Military Operationscited by 12
  9. 2024LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Surveycited by 12
  10. 2025Geo-OLM: Enabling Sustainable Earth Observation Studies with Cost-Efficient Open Language Models & State-Driven Workflowscited by 11
  11. 2024DisasterQA: A Benchmark for Assessing the performance of LLMs in Disaster Responsecited by 9
  12. 2025Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Responsecited by 9
22 more
  1. 2025Towards Evaluating Proactive Risk Awareness of Multimodal Language Modelscited by 6
  2. 2025A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptationcited by 5
  3. 2025RESPONSE: Benchmarking the Ability of Language Models to Undertake Commonsense Reasoning in Crisis Situationcited by 4
  4. 2024IncidentResponseGPT: Generating Traffic Incident Response Plans with Generative Artificial Intelligencecited by 3
  5. 2024No Size Fits All: The Perils and Pitfalls of Leveraging LLMs Vary with Company Sizecited by 3
  6. 2025Reimagining Urban Science: Scaling Causal Inference with Large Language Modelscited by 3
  7. 2024Scalable Interactive Machine Learning for Future Command and Controlcited by 2
  8. 2025Automating the loop in traffic incident management on highwaycited by 2
  9. 2025From Prediction to Foresight: The Role of AI in Designing Responsible Futurescited by 2
  10. 2026Adaptive Multilevel Twisted Sequential Monte Carlo for Rare Events Estimation in Language Modelscited by 2
  11. 2025GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?cited by 1
  12. 2025Building Safer Sites: A Large-Scale Multi-Level Dataset for Construction Safety Researchcited by 1
  13. 2026Risk-Conditioned Fine-Tuning of Large Language Modelscited by 1
  14. 2025ClimaEmpact: Domain-Aligned Small Language Models and Datasets for Extreme Weather Analyticscited by 0
  15. 2025Automated Traffic Incident Response Plans using Generative Artificial Intelligence: Part 1 -- Building the Incident Response Benchmarkcited by 0
  16. 2025A Dynamic Fusion Model for Consistent Crisis Responsecited by 0
  17. 2025Human-AI Use Patterns for Decision-Making in Disaster Scenarios: A Systematic Reviewcited by 0
  18. 2025LEO-RobotAgent: A General-purpose Robotic Agent for Language-driven Embodied Operatorcited by 0
  19. 2026Learning social norms enhances compatibility in dynamic human-AI coordinationcited by 0
  20. 2026From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMscited by 0
  21. 2026Agentic AI for Safety-critical Multi-drone Systems: Challenges and Opportunitiescited by 0
  22. 2026GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answeringcited by 0