Generative Language Models for Paragraph-Level Question Generation

Understand

Powerful generative models have led to recent progress in question generation (QG).

• However, it is difficult to measure advances in QG research since there are no standardized resources that allow a uniform comparison among approaches.
• In this paper, we introduce QG-Bench, a multilingual and multidomain benchmark for QG that unifies existing question answering datasets by converting them to a standard QG setting.
• It includes general-purpose datasets such as SQuAD for English, datasets from ten domains and two styles, as well as datasets in eight different languages.