224 citations · 1.1k across the 33 of their papers we have counts for
3 papers · 2 filters
A Joint Model for Question Answering and Question Generation
Tong Wang, Xingdi Yuan, Adam Trischler
We propose a generative machine comprehension model that learns jointly to ask and answer questions based on documents. The proposed model uses a sequence-to-sequence framework tha…
Neural Models for Key Phrase Detection and Question Generation
Sandeep Subramanian, Tong Wang, Xingdi Yuan +3
We propose a two-stage neural model to tackle question generation from documents. First, our model estimates the probability that word sequences in a document are ones that a human…
Machine Comprehension by Text-to-Text Neural Question Generation
Xingdi Yuan, Tong Wang, Caglar Gulcehre +5
We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervis…