Explainable Multi-hop Question Generation: An End-to-End Approach without Intermediate Question Labeling

arXiv:2404.00571v1 Announce Type: new
Abstract: In response to the increasing use of interactive artificial intelligence, the demand for the capacity to handle complex questions has increased. Multi-hop question generation aims to generate complex questions that requires multi-step reasoning over several documents. Previous studies have predominantly utilized end-to-end models, wherein questions are decoded based on the representation of context documents. However, these approaches lack the ability to explain the reasoning process behind the generated multi-hop questions. Additionally, the question rewriting approach, …

abstract artificial artificial intelligence arxiv capacity cs.cl demand documents generate intelligence interactive intermediate labeling question questions reasoning studies type