31 citations · 89 across the 6 of their papers we have counts for
4 papers · 1 filter
Unsupervised Domain Adaptation of Language Models for Reading Comprehension
Kosuke Nishida, Kyosuke Nishida, Itsumi Saito +2
This study tackles unsupervised domain adaptation of reading comprehension (UDARC). Reading comprehension (RC) is a task to learn the capability for question answering with textual…
A Simple but Effective Method to Incorporate Multi-turn Context with BERT for Conversational Machine Comprehension
Yasuhito Ohsugi, Itsumi Saito, Kyosuke Nishida +2
Conversational machine comprehension (CMC) requires understanding the context of multi-turn dialogue. Using BERT, a pre-training language model, has been successful for single-turn…
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction
Kosuke Nishida, Kyosuke Nishida, Masaaki Nagata +4
Question answering (QA) using textual sources for purposes such as reading comprehension (RC) has attracted much attention. This study focuses on the task of explainable multi-hop…
Multi-style Generative Reading Comprehension
Kyosuke Nishida, Itsumi Saito, Kosuke Nishida +4
This study tackles generative reading comprehension (RC), which consists of answering questions based on textual evidence and natural language generation (NLG). We propose a multi-…