31 citations · 145 across the 10 of their papers we have counts for
10 papers
VisualMRC: Machine Reading Comprehension on Document Images
Ryota Tanaka, Kyosuke Nishida, Sen Yoshida
Recent studies on machine reading comprehension have focused on text-level understanding but have not yet reached the level of human understanding of the visual layout and content…
A Transformer-based Audio Captioning Model with Keyword Estimation
Yuma Koizumi, Ryo Masumura, Kyosuke Nishida +2
One of the problems with automated audio captioning (AAC) is the indeterminacy in word selection corresponding to the audio event/scene. Since one acoustic event/scene can be descr…
Abstractive Summarization with Combination of Pre-trained Sequence-to-Sequence and Saliency Models
Itsumi Saito, Kyosuke Nishida, Kosuke Nishida +1
Pre-trained sequence-to-sequence (seq-to-seq) models have significantly improved the accuracy of several language generation tasks, including abstractive summarization. Although th…
Length-controllable Abstractive Summarization by Guiding with Summary Prototype
Itsumi Saito, Kyosuke Nishida, Kosuke Nishida +5
We propose a new length-controllable abstractive summarization model. Recent state-of-the-art abstractive summarization models based on encoder-decoder models generate only one sum…
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…