论文标题
更好的检索可能不会导致更好的问题回答
Better Retrieval May Not Lead to Better Question Answering
论文作者
论文摘要
最近在开放域问答（QA）问题中取得了很大进展，这些问题需要信息检索（IR）和阅读理解（RC）。改善系统性能的一种流行方法是提高IR阶段检索到上下文的质量。在这项工作中，我们表明，对于需要多跳推理的具有挑战性的开放域QA数据集而言，这种常见方法令人惊讶地无效 - 提高检索到的上下文的质量几乎无法改善系统的性能。我们进一步分析系统的行为以识别潜在原因。
Considerable progress has been made recently in open-domain question answering (QA) problems, which require Information Retrieval (IR) and Reading Comprehension (RC). A popular approach to improve the system's performance is to improve the quality of the retrieved context from the IR stage. In this work we show that for StrategyQA, a challenging open-domain QA dataset that requires multi-hop reasoning, this common approach is surprisingly ineffective -- improving the quality of the retrieved context hardly improves the system's performance. We further analyze the system's behavior to identify potential reasons.
