Ryo Yoshida

Ph.D student at the University of Tokyo / Jool Corp. Co-founder

Language Computational Cognitive Science Laboratory (Oseki Laboratory)

Department of Language and Information Sciences, Graduate School of Arts and Sciences, University of Tokyo

Biography

I’m Ryo Yoshida, a Ph.D student at the Department of Language and Information Sciences, Graduate School of Arts and Sciences, University of Tokyo. I’m working with Yohei Oseki on natural language processing, cognitive modeling, and syntactic supervision.

Interests

Natural Language Processing
Cognitive Modeling
Syntactic Supervision

Education

Doctor of Arts, April 2023 - Present

Department of Language and Information Sciences, Graduate School of Arts and Sciences, University of Tokyo
Master of Arts, April 2021 - March 2023

Department of Language and Information Sciences, Graduate School of Arts and Sciences, University of Tokyo
Bachelor of Arts, April 2017 - March 2021

Department of Humanities and Social Sciences, College of Arts and Sciences, University of Tokyo

Skills

Python

4 years

R

A little

Haskell

Beginner

Experience

CTO

Jool Corp.

Apr 2022 – Mar 2024 Kyoto

学術専門職員

The University of Tokyo

Nov 2021 – Mar 2023 Tokyo

AI engineering internship

ELYZA, Inc.

May 2020 – Oct 2022 Tokyo

Grants

Japan Society for Promotion of Science (JSPS) Research Fellowship for Young Scientists (DC2)

200,000 yen / month + 1,500,000 yen
April 2024 - March 2026

Apr 1, 2024

日本学生支援機構奨学金特に優れた業績による返還免除（全額免除）

1,200,000 yen

Jul 7, 2023

グリーントランスフォーメーション (GX) を先導する高度人材育成 (SPRING GX)

180,000 yen / month + 340,000 yen / year
April 2023 - March 2026

Apr 1, 2023

Recent Publications

Ryo Yoshida, Taiga Someya, Yohei Oseki (2024). Tree-Planted Transformers: Unidirectional Transformer Language Models with Implicit Syntactic Supervision. Findings of the Association for Computational Linguistics: ACL 2024 (acceptance rate: ??%).

Preprint

Kohei Kajikawa, Ryo Yoshida, Yohei Oseki (2024). Dissociating Syntactic Operations via Composition Count. Annual Meeting of the Cognitive Science Society (oral presentation acceptance rate: 19%).

Taiga Someya, Ryo Yoshida, Yohei Oseki (2024). Targeted Syntactic Evaluations on the Chomsky Hierarchy. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING) (acceptance rate: 44%).

PDF Cite

Yushi Sugimoto, Ryo Yoshida, Hyeonjeong Jeong, Masatoshi Koizumi, Jonathan R. Brennan, Yohei Oseki (2023). Localizing Syntactic Composition with Left-Corner Recurrent Neural Network Grammars. Neurobiology of Language.

PDF Cite DOI

Ryo Yoshida, Yohei Oseki (2022). Composition, Attention, or Both?. Findings of the Association for Computational Linguistics: EMNLP 2022 (acceptance rate: 36%).

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