AI4Fire: Evaluating Large Language Models on Wildfire Tasks

arXiv:2610.10946 · cs.CL, cs.LG · Submitted 2026-10-07 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-10-07

Updated: 2026-10-07

Code: https://github.com/yzhao062/AI4Fire

Terminology

• Accuracy — 80× in this paper · explained in 1 episode
• Core — 80× in this paper · explained in 2 episodes
• Benchmark — 54× in this paper · explained in 2 episodes
• Grounding — 35× in this paper · explained in 3 episodes
• Calibration — 15× in this paper · explained in 7 episodes
• Clustering — 7× in this paper · explained in 2 episodes
• Text-to-SQL — 5× in this paper · explained in 3 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Failure Modes — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Multi-Agent System — 2× in this paper · explained in 5 episodes
• RAG — 2× in this paper · explained in 3 episodes
• Verification — 2× in this paper · explained in 2 episodes
• AUC — 1× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Causal Reasoning — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Failure Taxonomy — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Thinking mode — 1× in this paper · explained in 2 episodes

Sources

• WildfireVLM: AI-powered Analysis for Early Wildfire Detection and Risk Assessment Using Satellite Imagery
• Qwen3-VL Technical Report
• Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response
• FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision
• Organizational Principles Enable Collective Intelligence in Embodied AI
• Multilingual Agent System for Inclusive Wildfire Evacuation Guidance
• IC-EO: Interpretable Code-based assistant for Earth Observation
• Inaugural MOASEI Competition at AAMAS'2025: A Technical Report
• Evaluating Large Language Model Performance on International Maritime Dangerous Goods Code Compliance
• Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations
• Does Your Wildfire Prediction Model Actually Work, or Just Score Well?
• DisasterBench: A Multimodal Benchmark for UAV-Based Disaster Response in Complex Environments

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