# Recent Advances in Neural Question Generation

**Authors:** Liangming Pan, Wenqiang Lei, Tat-Seng Chua, Min-Yen Kan  
**arXiv:** [1905.08949](https://arxiv.org/abs/1905.08949)  
**Date:** 2019-05-22  
**Summary page:** https://www.summarizepaper.com/fr/paper/1905.08949v1/

## Abstract

Emerging research in Neural Question Generation (NQG) has started to integrate a larger variety of inputs, and generating questions requiring higher levels of cognition. These trends point to NQG as a bellwether for NLP, about how human intelligence embodies the skills of curiosity and integration. We present a comprehensive survey of neural question generation, examining the corpora, methodologies, and evaluation methods. From this, we elaborate on what we see as emerging on NQG's trend: in terms of the learning paradigms, input modalities, and cognitive levels considered by NQG. We end by pointing out the potential directions ahead.