5 Hands-on 3: Building a customizable chatbot using large language models.

IF 2.9 2区农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE

Journal of animal science Pub Date : 2025-10-05 DOI:10.1093/jas/skaf300.089

John Gottula, Shelly Hunt

引用次数: 0

Abstract

Researchers and teachers are often dismayed by outrageous answers received from large language models (LLMs). In this workshop, you will learn how to arm an LLM with specific knowledge, such as from an animal agriculture research program. Participants’ expected learning outcomes are to 1) become familiar with natural language processing 2) learn best practices for LLM augmentation 3) understand how building a knowledgeable chatbot could apply to your research, teaching or extension program

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5实践3：使用大型语言模型构建可定制的聊天机器人

研究人员和教师经常对从大型语言模型（llm）收到的离谱的答案感到沮丧。在本次研讨会中，您将学习如何武装法学硕士与特定的知识，如从动物农业研究计划。参与者的预期学习成果是：1)熟悉自然语言处理；2)学习法学硕士增强的最佳实践；3)了解如何构建知识渊博的聊天机器人应用于您的研究、教学或扩展项目

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of animal science 农林科学-奶制品与动物科学

CiteScore

4.80

自引率

12.10%

发文量

1589

审稿时长

3 months

期刊介绍： The Journal of Animal Science (JAS) is the premier journal for animal science and serves as the leading source of new knowledge and perspective in this area. JAS publishes more than 500 fully reviewed research articles, invited reviews, technical notes, and letters to the editor each year. Articles published in JAS encompass a broad range of research topics in animal production and fundamental aspects of genetics, nutrition, physiology, and preparation and utilization of animal products. Articles typically report research with beef cattle, companion animals, goats, horses, pigs, and sheep; however, studies involving other farm animals, aquatic and wildlife species, and laboratory animal species that address fundamental questions related to livestock and companion animal biology will be considered for publication.