Yuki Arase


Associate professor, Osaka University

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荒瀬 由紀

ビッグデータ工学講座 (鬼塚研究室)

Email: arase[at]ist.osaka-u.ac.jp
Twitter: @Yuki_arase

2006年大阪大学工学部電子情報エネルギー工学科卒業。 2007年同大学院情報科学研究科博士前期課程、2010年同博士後期課程修了。博士(情報科学)。同年、北京のMicrosoft Researchに入社、自然言語処理に関する研究開発に従事。 2014年より大阪大学大学院情報科学研究科マルチメディア工学専攻准教授、現在に至る。 言い換え表現認識および生成、それらを応用した言語学習支援、医療言語処理に興味を持つ。

2022年10月もしくは2023年4月スタートの博士後期課程学生を募集しています。興味のある方は業績リスト付きのCVをお送りください。 ※ 研究生の募集はしていません。

Publications / ACL Anthology / Google Scholar / Semantic Scholar


(Last update: 2023/05/31)


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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