论文标题
答案合并：配方和基准测试
Answer Consolidation: Formulation and Benchmarking
论文作者
论文摘要
当前的问题回答（QA）系统主要考虑单回答场景，其中每个问题都被认为与一个正确的答案配对。但是，在许多现实世界中的QA应用程序中，会出现多种答案方案，其中将答案合并为全面且非冗余的答案集是一个更有效的用户界面。在本文中，我们制定了答案合并问题，其中答案被分配为多组，每个组都代表答案集的不同方面。然后，鉴于此分区，可以通过从每个组中选择一个答案来构建一组全面且非冗余的答案。为了启动答案合并的研究，我们构建了一个由4,699个问题和24,006个句子组成的数据集，并评估了多个模型。尽管表现最好的监督模型表现出色，但我们仍然认为这项任务有进一步改进的空间。
Current question answering (QA) systems primarily consider the single-answer scenario, where each question is assumed to be paired with one correct answer. However, in many real-world QA applications, multiple answer scenarios arise where consolidating answers into a comprehensive and non-redundant set of answers is a more efficient user interface. In this paper, we formulate the problem of answer consolidation, where answers are partitioned into multiple groups, each representing different aspects of the answer set. Then, given this partitioning, a comprehensive and non-redundant set of answers can be constructed by picking one answer from each group. To initiate research on answer consolidation, we construct a dataset consisting of 4,699 questions and 24,006 sentences and evaluate multiple models. Despite a promising performance achieved by the best-performing supervised models, we still believe this task has room for further improvements.
