Domain adaptive multi-task transformer for low-resource machine reading comprehension
Authors:
- Ziwei BaiZBZiwei Bai
- Baoxun WangBWBaoxun Wang
- Zongsheng WangZWZongsheng Wang
- Caixia YuanCYCaixia Yuan
- Xiaojie WangXWXiaojie Wang
- 19 August 2022
- journal article
- research article
- Published by Elsevier in Neurocomputing
- Vol. 509, 46-55
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (62076032)
This publication has 23 references indexed in Scilit:
- Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts2018
- Supervised and Unsupervised Transfer Learning for Question Answering2018
- Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation2017
- Adversarial Multi-task Learning for Text Classification2017
- NewsQA: A Machine Comprehension Dataset2017
- Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension2017
- SQuAD: 100,000+ Questions for Machine Comprehension of Text2016
- Learning with digital texts: Exploring the impact of prior domain knowledge and reading comprehension ability on navigation and learning outcomesComputers in Human Behavior, 2015
- Direction selectivity in V1 of alert monkeys: evidence for parallel pathways for motion processingThe Journal of Physiology, 2007
- Integrating structured biological data by Kernel Maximum Mean DiscrepancyBioinformatics, 2006