Yuki Arase


Professor, Tokyo Institute of Technology

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Yuki Arase

Professor (Japanese page)

School of Computing, Tokyo Institute of Technology, Japan

Arase Lab

Email: arase@ (add the domain: c.titech.ac.jp)

Twitter: @Yuki_arase

I am a professor at the School of Computing, Tokyo Institute of Technology, Japan. After obtaining my PhD in Information Science from Osaka University (2010), I worked for Microsoft Research Asia, where I started NLP research that continues to captivate me to this day. My research interests focus on paraphrasing and NLP technology for language education and healthcare.

I’m recruiting PhD students and postdocs. Please send me your CV with a publication list if you are interested. Note that we do not have “research student” positions.

Publications / CV / ACL Anthology / Google Scholar / Semantic Scholar


(Last update: 2024/04/01)


For more details, please see Research page.

Paraphrase generation & recognition

Paraphrasing takes various forms of monolingual text transformations, such as text simplification, rewriting, and style transfer. We work on both recognition and generation. The core technologies are intelligent phrase alignment and controllable paraphrase generation.

Related papers: DIRECT, phrase alignment, Round-trip translation for paraphrasing, SAPPHIRE

Representation learning

Vector representation of words, phrases, and sentences are the very basis for NLP research. We study

  1. sophisticated representations for word meaning in context and multilingual sentences,
  2. efficient pre-trained models for words and phrases, and
  3. representations for few-shot learning.

Related papers: WiC representation, disentangling sentence meaning, transfer fine-tuning, label representation for few-shot learning, tiny word embedding

NLP for language education & learning

As a central application of our research outcomes, we develop technologies for language learning and education supports. Our technology covers from fine-grained lexical-level transformations to coarse-grained text-level processing.

Related papers: definition generation, controllable text simplification, CEFR-based lexical simplification, fill-in-the-blank quiz generation

Selected Recent Publications

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