让非技术人员用自然语言快速分析表格数据
Genicious: Contextual Few-shot Prompting for Insights Discovery
- 采用上下文少样本提示技术，提升查询准确率
- 在延迟、准确率和可扩展性上表现更优
- 适合需要安全分析数据的业务决策者
数据与洞察发现对现代组织的决策至关重要。我们提出 Genicious，一个基于大模型的交互式界面，使用户能以自然语言与表格数据集交互并提出复杂查询。通过对比多种提示策略与语言模型，我们开发出端到端工具，采用上下文少样本提示，在延迟、准确率和可扩展性方面表现更优。Genicious 使利益相关者能够高效探索、分析和可视化数据集，同时通过基于角色的访问控制和 Text-to-SQL 方法保障数据安全。
原文摘要 · Abstract (English)
Data and insights discovery is critical for decision-making in modern organizations. We present Genicious, an LLM-aided interface that enables users to interact with tabular datasets and ask complex queries in natural language. By benchmarking various prompting strategies and language models, we have developed an end-to-end tool that leverages contextual few-shot prompting, achieving superior performance in terms of latency, accuracy, and scalability. Genicious empowers stakeholders to explore, analyze and visualize their datasets efficiently while ensuring data security through role-based access control and a Text-to-SQL approach.
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