4 citations · 23 across the 15 of their papers we have counts for
15 papers
Japanese Lexical Complexity for Non-Native Readers: A New Dataset
Yusuke Ide, Masato Mita, Adam Nohejl +2
Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale. It plays a vital role in simplifying or annotating complex wo…
Second Language Acquisition of Neural Language Models
Miyu Oba, Tatsuki Kuribayashi, Hiroki Ouchi +1
With the success of neural language models (LMs), their language acquisition has gained much attention. This work sheds light on the second language (L2) acquisition of LMs, while…
Arukikata Travelogue Dataset with Geographic Entity Mention, Coreference, and Link Annotation
Shohei Higashiyama, Hiroki Ouchi, Hiroki Teranishi +9
Geoparsing is a fundamental technique for analyzing geo-entity information in text. We focus on document-level geoparsing, which considers geographic relatedness among geo-entity m…
NAIST Academic Travelogue Dataset
Hiroki Ouchi, Hiroyuki Shindo, Shoko Wakamiya +5
We have constructed NAIST Academic Travelogue Dataset (ATD) and released it free of charge for academic research. This dataset is a Japanese text dataset with a total of over 31 mi…
N-best Response-based Analysis of Contradiction-awareness in Neural Response Generation Models
Shiki Sato, Reina Akama, Hiroki Ouchi +3
Avoiding the generation of responses that contradict the preceding context is a significant challenge in dialogue response generation. One feasible method is post-processing, such…
Instance-Based Neural Dependency Parsing
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi +4
Interpretable rationales for model predictions are crucial in practical applications. We develop neural models that possess an interpretable inference process for dependency parsin…
Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution
Ryuto Konno, Shun Kiyono, Yuichiroh Matsubayashi +2
Masked language models (MLMs) have contributed to drastic performance improvements with regard to zero anaphora resolution (ZAR). To further improve this approach, in this study, w…
An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution
Ryuto Konno, Yuichiroh Matsubayashi, Shun Kiyono +3
One critical issue of zero anaphora resolution (ZAR) is the scarcity of labeled data. This study explores how effectively this problem can be alleviated by data augmentation. We ad…
Corruption Is Not All Bad: Incorporating Discourse Structure into Pre-training via Corruption for Essay Scoring
Farjana Sultana Mim, Naoya Inoue, Paul Reisert +2
Existing approaches for automated essay scoring and document representation learning typically rely on discourse parsers to incorporate discourse structure into text representation…
Embeddings of Label Components for Sequence Labeling: A Case Study of Fine-grained Named Entity Recognition
Takuma Kato, Kaori Abe, Hiroki Ouchi +3
In general, the labels used in sequence labeling consist of different types of elements. For example, IOB-format entity labels, such as B-Person and I-Person, can be decomposed int…
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi +4
Interpretable rationales for model predictions play a critical role in practical applications. In this study, we develop models possessing interpretable inference process for struc…
Evaluating Dialogue Generation Systems via Response Selection
Shiki Sato, Reina Akama, Hiroki Ouchi +2
Existing automatic evaluation metrics for open-domain dialogue response generation systems correlate poorly with human evaluation. We focus on evaluating response generation system…
Suspicious News Detection Using Micro Blog Text
Tsubasa Tagami, Hiroki Ouchi, Hiroki Asano +9
We present a new task, suspicious news detection using micro blog text. This task aims to support human experts to detect suspicious news articles to be verified, which is costly b…
A Span Selection Model for Semantic Role Labeling
Hiroki Ouchi, Hiroyuki Shindo, Yuji Matsumoto
We present a simple and accurate span-based model for semantic role labeling (SRL). Our model directly takes into account all possible argument spans and scores them for each label…
Addressee and Response Selection for Multilingual Conversation
Motoki Sato, Hiroki Ouch, Yuta Tsuboi
Developing conversational systems that can converse in many languages is an interesting challenge for natural language processing. In this paper, we introduce multilingual addresse…