As part of the Department of Intelligence Science and Technology's Artificial Intelligence online course, we held Session 3 Natural Language Processing †

We will present the following papers at COLING2020 (2020/12/8-13) †

• Raj Dabre, Chenhui Chu, Anoop Kunchukuttan:
  Multilingual Neural Machine Translation (Tutorial)

• Nobuhiro Ueda, Daisuke Kawahara and Sadao Kurohashi:
  BERT-based Cohesion Analysis of Japanese Texts

• Oleksandr Harust, Yugo Murawaki and Sadao Kurohashi:
  Native-like Expression Identification by Contrasting Native and Proficient Second Language Speakers

The following papers are accepted by EMNLP2020 Findings †

• Fei Cheng, Masayuki Asahara, Ichiro Kobayashi and Sadao Kurohashi:
  Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning
• Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara and Sadao Kurohashi:
  Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction

We will present the following papers at EMNLP2020 (2020/11/8-12) †

• Kazumasa Omura, Daisuke Kawahara and Sadao Kurohashi:
  A Method for Building a Commonsense Inference Dataset based on Basic Events
• Yugo Murawaki:
  Latent Geographical Factors for Analyzing the Evolution of Dialects in Contact

The following paper received the Young Researcher award of the 244-th meeting of IPSJ Natural Language Processing(link in Japanese) (2020/7) †

• Takumi Yoshikoshi, Daisuke Kawahara and Sadao Kurohashi:
  Multilingualization of a Natural Language Inference Dataset Using Machine Translation

Search Engine Infrastructure based on Deep Natural Language Processing †

The essential purpose of information retrieval is not to retrieve just a relevant document but to acquire the information or knowledge in the document. We have been developing a next-generation infrastructure of information retrieval on the basis of the following techniques of deep natural language processing: precise processing based not on words but on predicate-argument structures, identifying the variety of linguistic expressions and providing a bird's-eye view of search results via clustering and interaction.

Machine Translation †

To bring automatic translation by computers to the level of human translation, we have been studying next-generation methodology of machine translation on the basis of text understanding and a large collection of translation examples. We have already accomplished practical translation on the domain of travel conversation, and constructed a translation-aid system that can be used by experts of patent translation.