arXiv:2507.20520cs.CLcs.AI2025-07被引 2

首个专为水产养殖设计的大模型,助力行业智能决策

AQUA: A Large Language Model for Aquaculture & Fisheries

  • 构建AQUADAPT框架,融合专家知识与大模型生成高质量合成数据
  • 首次实现面向水产养殖场景的专用大语言模型,支持多任务应用
  • 适合养殖从业者、科研人员及政策制定者使用

水产养殖在全球粮食安全和沿海经济中发挥着关键作用,提供可持续的蛋白质来源。随着需求增长,行业面临疾病爆发、喂养效率低、人力成本上升、物流不畅以及孵化环节高死亡率、水质控制差等挑战。尽管人工智能取得进展,现有机器学习方法仍难以应对水产养殖特有的复杂性。为此,我们提出AQUA——首个专为水产养殖设计的大语言模型,服务于养殖户、研究人员和产业实践者。核心是AQUADAPT(数据获取、处理与调优)框架,通过结合专家知识、大规模语言模型和自动化评估技术,生成并优化高质量合成数据。本工作为基于大语言模型的水产养殖研究、咨询系统和决策工具奠定了基础。

原文摘要 · Abstract (English)

Aquaculture plays a vital role in global food security and coastal economies by providing sustainable protein sources. As the industry expands to meet rising demand, it faces growing challenges such as disease outbreaks, inefficient feeding practices, rising labor costs, logistical inefficiencies, and critical hatchery issues, including high mortality rates and poor water quality control. Although artificial intelligence has made significant progress, existing machine learning methods fall short of addressing the domain-specific complexities of aquaculture. To bridge this gap, we introduce AQUA, the first large language model (LLM) tailored for aquaculture, designed to support farmers, researchers, and industry practitioners. Central to this effort is AQUADAPT (Data Acquisition, Processing and Tuning), an Agentic Framework for generating and refining high-quality synthetic data using a combination of expert knowledge, largescale language models, and automated evaluation techniques. Our work lays the foundation for LLM-driven innovations in aquaculture research, advisory systems, and decision-making tools.

大模型水产养殖智能决策

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