activity
20182021
most citedRetrieve-and-Read: Multi-task Learning of Information Retrieval and Reading Comprehension

31 citations · 145 across the 10 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CL2019★ 15 cited

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…

cs.CL2019★ 2 cited

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…

cs.CL2019★ 5 cited

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…

cs.CY2019★ 20 cited

Personalized Visited-POI Assignment to Individual Raw GPS Trajectories

Jun Suzuki, Yoshihiko Suhara, Hiroyuki Toda +1

Knowledge discovery from GPS trajectory data is an important topic in several scientific areas, including data mining, human behavior analysis, and user modeling. This paper propos…

cs.CL2019★ 12 cited

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-…