评估大型语言模型聊天机器人在生成普通语言摘要方面的能力
Himel Mondal1, Gaurav Gupta2, Pradosh Kumar Sarangi3
1Physiology, All India Institute of Medical Sciences, Deoghar, IND.
Cureus
|April 22, 2025
概括
大型语言模型 (LLM) 聊天机器人可以生成简单语言摘要 (PLSs),可读性提高,质量与人类编写的版本相当. 这些人工智能工具提供了显著的好处,特别是对于非母语英语人士和发展中国家的研究人员.
科学领域:
- 科学传播是科学传播.
- 研究中的人工智能.
背景情况:
- 简单的语言摘要 (PLSs) 对于使科学研究可供非专家受众访问至关重要.
- 制定有效的PLS存在挑战,特别是对于非英语母语的研究人员.
- 大型语言模型 (LLM) 聊天机器人帮助PLS生成的潜力尚未得到充分探索.
研究的目的:
- 将人类编写的PLS的质量和可读性与各种LLM聊天机器人生成的PLS进行比较.
- 评估LLM聊天机器人在制作可访问的科学摘要方面的有效性.
主要方法:
- 一项横截面研究比较了30个人类编写的PLS与6个LLM聊天机器人 (ChatGPT,Claude,Copilot,Gemini,Meta AI,Perplexity) 所生成的PLS.
- 使用Flesch阅读易度 (FR) 评分和Flesch-Kincaid (FK) 等级来评估可读性.
- 文本质量由三个作者根据预先定义的标准进行评估.
主要成果:
- 与人写的PLS相比,LLM生成的PLS显示了较低的FK等级和更高的FR易度得分 (p < 0.0001).
- 在人类生成的PLS和来自单个LLM聊天机器人的PLS之间,没有发现总体质量评分的统计学上显著差异.
- LLM 聊天机器人产生了与人类编写的质量相当的 PLS.
结论:
- LLM聊天机器人可以生成具有增强可读性的PLS,使研究可访问较低教育背景的个人.
- 由LLM生成的PLS的质量与人写的摘要相当.
- 作者可以利用LLM聊天机器人来生成PLS,对发展中国家的研究人员来说尤其有利,尽管准确性检查是必不可少的.
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