法学士比较器:对大型语言模型并排评估的交互分析
IEEE transactions on visualization and computer graphics
|September 10, 2024
概括
评估大型语言模型 (LLM) 是一个挑战. LLM Comparator是一个新的视觉工具,可以帮助研究人员了解LLM的性能差异,并改进模型开发.
科学领域:
- 人工智能的人工智能
- 人与计算机的交互
- 数据可视化 数据可视化
背景情况:
- 使用自动并排比较 (LLM-as-a-judge) 评估大型语言模型 (LLM) 是有希望的,但面临着可扩展性和可解释性问题.
- 目前的方法阻碍了对模型性能的深入分析和理解不同LLM输出背后的原因.
研究的目的:
- 介绍LLM Comparator,这是一个新的视觉分析工具,旨在解决分析并排LLM评估的挑战.
- 提供分析工作流程,使用户能够理解LLM在性能和响应生成方面何时以及为什么有所不同.
主要方法:
- 通过与谷歌的法学士从业人员的合作,反复设计和开发法学士比较器.
- 整合视觉分析技术,以促进对单个示例的深入分析和对大型数据集的概述.
- 以用户为中心的定性反收集和整合到工具的改进过程中.
主要成果:
- 在LLM Comparator中,可以对LLM生成的个别例子进行深入分析.
- 该工具使用户能够视觉概述和灵活切割评估数据,帮助识别模式.
- 定性反证实了该工具在制定假设和获得LLM改进见解方面的实用性.
结论:
- 士学位比较器提高了士学位评估的可扩展性和可解释性.
- 该工具使研究人员和开发人员能够更深入地了解LLM行为,并推动模型的改进.
- LLM Comparator已经集成到谷歌的LLM评估平台中,并为更广泛的采用提供开源.
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