no code implementations • Findings (EMNLP) 2021 • Masato Umakoshi, Yugo Murawaki, Sadao Kurohashi
Parallel texts of Japanese and a non-pro-drop language have the potential of improving the performance of Japanese zero anaphora resolution (ZAR) because pronouns dropped in the former are usually mentioned explicitly in the latter.
no code implementations • EMNLP 2020 • Yugo Murawaki
Analyzing the evolution of dialects remains a challenging problem because contact phenomena hinder the application of the standard tree model.
1 code implementation • 29 Feb 2024 • Yugo Murawaki
Bayesian approaches to reconstructing the evolutionary history of languages rely on the tree model, which assumes that these languages descended from a common ancestor and underwent modifications over time.
1 code implementation • 12 Nov 2022 • Jumon Nozaki, Yugo Murawaki
Previous studies on neural linguistic steganography, except Ueoka et al. (2021), overlook the fact that the sender must detokenize cover texts to avoid arousing the eavesdropper's suspicion.
1 code implementation • NAACL 2021 • Honai Ueoka, Yugo Murawaki, Sadao Kurohashi
With advances in neural language models, the focus of linguistic steganography has shifted from edit-based approaches to generation-based ones.
no code implementations • COLING 2020 • Oleksandr Harust, Yugo Murawaki, Sadao Kurohashi
We propose a novel task of native-like expression identification by contrasting texts written by native speakers and those by proficient second language speakers.
no code implementations • EMNLP (NLP-COVID19) 2020 • Akiko Aizawa, Frederic Bergeron, Junjie Chen, Fei Cheng, Katsuhiko Hayashi, Kentaro Inui, Hiroyoshi Ito, Daisuke Kawahara, Masaru Kitsuregawa, Hirokazu Kiyomaru, Masaki Kobayashi, Takashi Kodama, Sadao Kurohashi, Qianying Liu, Masaki Matsubara, Yusuke Miyao, Atsuyuki Morishima, Yugo Murawaki, Kazumasa Omura, Haiyue Song, Eiichiro Sumita, Shinji Suzuki, Ribeka Tanaka, Yu Tanaka, Masashi Toyoda, Nobuhiro Ueda, Honai Ueoka, Masao Utiyama, Ying Zhong
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education.
no code implementations • ACL 2020 • Yu Tanaka, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi
User generated texts contain many typos for which correction is necessary for NLP systems to work.
no code implementations • LREC 2020 • Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi
BERT, a neural network-based language model pre-trained on large corpora, is a breakthrough in natural language processing, significantly outperforming previous state-of-the-art models in numerous tasks.
General Classification Implicit Discourse Relation Classification +3
no code implementations • WS 2019 • Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi
Typical event sequences are an important class of commonsense knowledge.
no code implementations • IJCNLP 2019 • Jun Saito, Yugo Murawaki, Sadao Kurohashi
Recognizing affective events that trigger positive or negative sentiment has a wide range of natural language processing applications but remains a challenging problem mainly because the polarity of an event is not necessarily predictable from its constituent words.
no code implementations • 24 Jun 2019 • Yugo Murawaki
The annotation guidelines for Universal Dependencies (UD) stipulate that the basic units of dependency annotation are syntactic words, but it is not clear what are syntactic words in Japanese.
no code implementations • CL 2019 • Yugo Murawaki
We borrow the concept of representation learning from deep learning research, and we argue that the quest for Greenbergian implicational universals can be reformulated as the learning of good latent representations of languages, or sequences of surface typological features.
1 code implementation • EMNLP 2018 • Yugo Murawaki
Statistical phylogenetic models have allowed the quantitative analysis of the evolution of a single categorical feature and a pair of binary features, but correlated evolution involving multiple discrete features is yet to be explored.
no code implementations • COLING 2018 • Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi
Identifying discourse relations that are not overtly marked with discourse connectives remains a challenging problem.
General Classification Implicit Discourse Relation Classification +4
no code implementations • IJCNLP 2017 • Yugo Murawaki
Although features of linguistic typology are a promising alternative to lexical evidence for tracing evolutionary history of languages, a large number of missing values in the dataset pose serious difficulties for statistical modeling.
no code implementations • COLING 2016 • Kenji Yamauchi, Yugo Murawaki
Linguistic typology provides features that have a potential of uncovering deep phylogenetic relations among the world{'}s languages.
no code implementations • LREC 2016 • Yugo Murawaki, Shinsuke Mori
To address this problem, we propose to define a separate task that directly links given texts to an external resource, that is, wikification in the case of Wikipedia.