Big Data Engineering Laboratory

Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University

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Yuki Arase

Yuki Arase is an associate professor at the graduate school of information science and technology, Osaka University, Japan. She was previously an associate researcher at the natural language computing group of Microsoft Research Asia. Her primary research interest is in English/Japanese machine translation, paraphrasing, conversation systems, and educational applications for language learners. She earned her Ph. D. of Information Science at Osaka University in 2010 for research on presenting a large amount of information on small screens.

She enjoys yoga practice, always traveling with her yoga mat in her luggage trolley.

(Last update: 2020/07/08)

arase at ist.osaka-u.ac.jp
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News

New papers from our team:

1. S. Ohashi, J. Takayama, T. Kajiwara, C. Chu, Y. Arase. Text Classification with Negative Supervision, in Proc. of Annual Meeting of the Association for Computational Linguistics (ACL 2020), pp. 351–357 (July 2020).
2. Y. Arase, T. Kajiwara, and C. Chu. Annotation of Adverse Drug Reactions in Patients' Weblogs, in Proc. of International Conference on Language Resources and Evaluation (LREC 2020), pp. 6769–6776 (May 2020).

Phrase Alignment project

We are working on phrase alignment and its application.

• Project page
• Our phrase alignment annotation dataset is available at LDC (LDC2018T09)
• Fine-tuned BERT models with phrasal paraphrases are available at my GitHub page

Selected Recent Publications

The list of all publications is available here.

1. S. Ohashi, J. Takayama, T. Kajiwara, C. Chu, Y. Arase. Text Classification with Negative Supervision, in Proc. of Annual Meeting of the Association for Computational Linguistics (ACL 2020), pp. 351–357 (July 2020).
2. T. Kajiwara, B. Miura, and Y. Arase. Monolingual Transfer Learning via Bilingual Translators for Style-Sensitive Paraphrase Generation, in Proc. of the AAAI Conference on Artificial Intelligence (AAAI 2020), pp. 8042-8049, (Feb. 2020).
3. Y. Arase and J. Tsujii: Transfer Fine-Tuning: A BERT Case Study, Proc. of Conference on Empirical Methods in Natural Language Processing (EMNLP2019), pp. 5396–5407 (Nov. 2019).
4. J. Takayama, E. Nomoto, and Y. Arase: Dialogue Breakdown Detection Robust to Variations in Annotators and Dialogue Systems, Computer Speech & Language, Vol. 54, pp. 31-43 (Mar. 2019).
5. Y. Arase and J. Tsujii: SPADE: Evaluation Dataset for Monolingual Phrase Alignment, in Proc. of Language Resources and Evaluation Conference (LREC 2018), (May 2018).
6. Y. Arase and J. Tsujii: Monolingual Phrase Alignment on Parse Forests, in Proc. of Conference on Empirical Methods in Natural Language Processing (EMNLP 2017), pp. 1-11 (Sept. 2017).