Combining Data Generation and Active Learning for Low-Resource Question Answering

1 code implementation • 27 Nov 2022 • Maximilian Kimmich, Andrea Bartezzaghi, Jasmina Bogojeska, Cristiano Malossi, Ngoc Thang Vu

In this work, we propose a novel approach that combines data augmentation via question-answer generation with Active Learning to improve performance in low-resource settings, where the target domains are diverse in terms of difficulty and similarity to the source domain.

Active Learning Answer Generation +4