Title: WildfireGPT: Tailored Large Language Model for Wildfire Analysis Show Chinese title

Title: WildfireGPT：用于野火分析的定制大型语言模型

Abstract: The recent advancement of large language models (LLMs) represents a transformational capability at the frontier of artificial intelligence (AI) and machine learning (ML). However, LLMs are generalized models, trained on extensive text corpus, and often struggle to provide context-specific information, particularly in areas requiring specialized knowledge such as wildfire details within the broader context of climate change. For decision-makers and policymakers focused on wildfire resilience and adaptation, it is crucial to obtain responses that are not only precise but also domain-specific, rather than generic. To that end, we developed WildfireGPT, a prototype LLM agent designed to transform user queries into actionable insights on wildfire risks. We enrich WildfireGPT by providing additional context such as climate projections and scientific literature to ensure its information is current, relevant, and scientifically accurate. This enables WildfireGPT to be an effective tool for delivering detailed, user-specific insights on wildfire risks to support a diverse set of end users, including researchers, engineers, urban planners, emergency managers, and infrastructure operators. Show Chinese abstract

Abstract: 大型语言模型（LLMs）的最新进展代表了人工智能（AI）和机器学习（ML）前沿的一项变革性能力。然而，LLMs是通用模型，训练于广泛的文本语料库上，往往难以提供特定上下文的信息，特别是在需要专业知识的领域，例如气候变化背景下关于野火的细节。 对于专注于野火韧性和适应性的决策者和政策制定者来说，获取不仅精确而且领域特定的响应，而非通用信息，至关重要。 为此，我们开发了WildfireGPT，这是一种原型LLM代理，旨在将用户的查询转化为关于野火风险的可操作见解。我们通过提供额外的上下文信息，如气候预测和科学文献，来丰富WildfireGPT，以确保其信息的时效性、相关性和科学准确性。 这使得WildfireGPT成为一种有效的工具，能够为各种最终用户提供关于野火风险的详细且特定于用户的信息，支持包括研究人员、工程师、城市规划师、应急管理专家以及基础设施运营商在内的多样化用户群体。