TACR: A Table-alignment-based Cell-selection and Reasoning Model for Hybrid Question-Answering

Understand

Hybrid Question-Answering (HQA), which targets reasoning over tables and passages linked from table cells, has witnessed significant research in recent years.

• A common challenge in HQA and other passage-table QA datasets is that it is generally unrealistic to iterate over all table rows, columns, and linked passages to retrieve evidence.
• Such a challenge made it difficult for previous studies to show their reasoning ability in retrieving answers.
• To bridge this gap, we propose a novel Table-alignment-based Cell-selection and Reasoning model (TACR) for hybrid text and table QA, evaluated on the HybridQA and WikiTableQuestions datasets.