Unsupervised Multi-hop Question Answering by Question Generation

Cited by: 0|Bibtex|Views25|Links

Abstract:

Obtaining training data for Multi-hop Question Answering (QA) is extremely time-consuming and resource-intensive. To address this, we propose the problem of \textit{unsupervised} multi-hop QA, assuming that no human-labeled multi-hop question-answer pairs are available. We propose MQA-QG, an unsupervised question answering framework tha...More

Code:

Data:

Your rating :
0

 

Tags
Comments