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English(EN) ParetoChat: An LLM-Based Interface for Interactive Multi-Objective Optimization

LLM驱动的ParetoChat简化了多目标优化

研究人员开发了ParetoChat,这是一种利用大型语言模型(LLM)促进交互式多目标优化的新型接口。该系统将决策者的自然语言请求转换为优化工具的结构化参数。一项使用基于LLM的决策者代理的模拟研究表明,ParetoChat能够有效地引导用户找到符合其偏好的解决方案,在某些情况下优于传统方法。该接口有望弥合业务利益相关者与复杂优化软件之间的差距。 AI

影响 这个LLM接口可以简化业务用户的复杂优化任务,可能增加高级分析工具的采用。

排序理由 该项目是一篇研究论文,详细介绍了一种新的优化方法和接口。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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LLM驱动的ParetoChat简化了多目标优化

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该项目是一篇研究论文,详细介绍了一种新的优化方法和接口。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Gokhan Ceyhan ·

    ParetoChat:一个基于LLM的交互式多目标优化界面

    arXiv:2610.23062v1 Announce Type: new Abstract: Multi-objective optimization models are often deployed in settings where decision makers (DMs) must balance some conflicting criteria. In practice, however, stakeholders must translate their qualitative preferences between different…