ReQAP系统能跨多种数据源回答复杂个人问题。
The ReQAP System for Question Answering over Personal Information
- 递归分解问题，逐步构建可执行的操作树
- 利用轻量级语言模型精准理解并执行查询
- 可追踪答案来源，提升用户可信度与可解释性
个人设备中存储着大量信息，包括日历、购物记录、健康工具中的结构化数据，以及邮件和社交媒体中的非结构化内容。本文提出ReQAP系统，支持用户针对异构数据源提出的复杂问题，涉及过滤、连接和聚合操作。其独特之处在于递归分解问题，并增量构建用于执行的操作符树。问题解析和各个操作均采用轻量级语言模型，经过合理微调以提升性能。演示展示了对高级用户问题的强大处理能力，同时提供执行树中各操作的详细追踪。能够将答案追溯至原始数据源，对提升人类可理解性和用户信任至关重要。
原文摘要 · Abstract (English)
Personal information is abundant on users' devices, from structured data in calendar, shopping records or fitness tools, to unstructured contents in mail and social media posts. This works presents the ReQAP system that supports users with answers for complex questions that involve filters, joins and aggregation over heterogeneous sources. The unique trait of ReQAP is that it recursively decomposes questions and incrementally builds an operator tree for execution. Both the question interpretation and the individual operators make smart use of light-weight language models, with judicious fine-tuning. The demo showcases the rich functionality for advanced user questions, and also offers detailed tracking of how the answers are computed by the operators in the execution tree. Being able to trace answers back to the underlying sources is vital for human comprehensibility and user trust in the system.
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