论文标题
一项关于表和文本Hybridqa的调查：概念，方法，挑战和未来的方向
A Survey on Table-and-Text HybridQA: Concepts, Methods, Challenges and Future Directions
论文作者
论文摘要
表和文本混合问题回答（HybrIDQA）是一种常用且具有挑战性的NLP任务，通常在金融和科学领域中应用。早期研究的重点是将其他质量检查任务方法迁移到HybridQA，而随着进一步的研究，已经存在越来越多的HybridQA特异性方法。随着HybrIDQA的快速发展，系统的调查仍未探索，以总结主要技术并进一步进行进一步的研究。因此，我们介绍了这项工作，以总结当前的HybrIDQA基准和方法，然后分析该任务的挑战和未来方向。本文的贡献可以概括为三倍：（1）据我们的最佳知识，包括基准，方法和Hybridqa的挑战； （2）对现有系统进行合理比较以表达其优势和缺点的合理比较； （3）对未来方向的四个重要方面的挑战进行了详细分析。
Table-and-text hybrid question answering (HybridQA) is a widely used and challenging NLP task commonly applied in the financial and scientific domain. The early research focuses on migrating other QA task methods to HybridQA, while with further research, more and more HybridQA-specific methods have been present. With the rapid development of HybridQA, the systematic survey is still under-explored to summarize the main techniques and advance further research. So we present this work to summarize the current HybridQA benchmarks and methods, then analyze the challenges and future directions of this task. The contributions of this paper can be summarized in three folds: (1) first survey, to our best knowledge, including benchmarks, methods and challenges for HybridQA; (2) systematic investigation with the reasonable comparison of the existing systems to articulate their advantages and shortcomings; (3) detailed analysis of challenges in four important dimensions to shed light on future directions.
