论文标题
作弊者的碗：人类与计算机搜索策略的开放域问题回答
Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain Question Answering
论文作者
论文摘要
对于人类和计算机，回答开放域问题的第一步是从大型语料库中检索一组相关文档。但是，计算机使用的策略从根本上与人类不同。为了更好地理解这些差异，我们设计了一个用于数据收集的游戏界面 - 骗子的碗 - 人类回答了使用传统和现代搜索工具的复杂问题。我们收集人类搜索会议的数据集，分析人类搜索策略，并将其与最先进的多跳质量检查模型进行比较。人类在逻辑上查询，应用动态搜索链，并利用世界知识来增强搜索。我们展示了人类查询如何提高现有系统的准确性，并提出改善QA模型的未来设计。
For humans and computers, the first step in answering an open-domain question is retrieving a set of relevant documents from a large corpus. However, the strategies that computers use fundamentally differ from those of humans. To better understand these differences, we design a gamified interface for data collection -- Cheater's Bowl -- where a human answers complex questions with access to both traditional and modern search tools. We collect a dataset of human search sessions, analyze human search strategies, and compare them to state-of-the-art multi-hop QA models. Humans query logically, apply dynamic search chains, and use world knowledge to boost searching. We demonstrate how human queries can improve the accuracy of existing systems and propose improving the future design of QA models.
