研究人员开发了TwinBI，一个将大型语言模型（LLM）与商业智能（BI）仪表盘集成的框架，以改善分析交互。TwinBI创建仪表盘状态的数字孪生，使LLM代理能够在直接操作和自然语言查询之间保持上下文。这种集成旨在通过提供更丰富、感知状态的上下文来提高分析的可靠性和用户支持。 AI
影响 TwinBI的方法可以通过在不同交互模式下保持上下文来提高AI辅助数据分析的准确性和效率。
排序理由 该集群包含一篇详细介绍新框架及其评估的学术论文。
在 arXiv cs.MA (Multiagent) 阅读 →
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.13731v1 Announce Type: new Abstract: Business intelligence (BI) increasingly combines dashboard interaction with LLM-based assistance, but these two modes often fall out of sync during multi-step analysis. As users switch between direct dashboard manipulation and natur…
Business intelligence (BI) increasingly combines dashboard interaction with LLM-based assistance, but these two modes often fall out of sync during multi-step analysis. As users switch between direct dashboard manipulation and natural-language queries, it becomes difficult to pre…