Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain Question Answering

Autor:	He, Wanrong, Mao, Andrew, Boyd-Graber, Jordan
Rok vydání:	2022
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	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. Comment: Findings of EMNLP 2022
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2212.03296 Zobrazit plný text záznamu View this record from Arxiv