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Ryo Yoshida
Ryo Yoshida
Ph.D student at the University of Tokyo
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
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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
Grants
Recent Publications
Taiga Someya,
Ryo Yoshida,
Hitomi Yanaka,
Yohei Oseki
(2025).
Derivational Probing: Unveiling the Layer-wise Derivation of Syntactic Structures in Neural Language Models.
Proceedings of the 29th Conference on Computational Natural Language Learning (acceptance rate: 18.4%).
Masato Mita,
Ryo Yoshida,
Yohei Oseki
(2025).
Developmentally-plausible Working Memory Shapes a Critical Period for Language Acquisition.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (acceptance rate: 20.3%).
Ryo Yoshida,
Shinnosuke Isono,
Kohei Kajikawa,
Taiga Someya,
Yushi Sugimoto,
Yohei Oseki
(2025).
If Attention Serves as a Cognitive Model of Human Memory Retrieval, What is the Plausible Memory Representation?.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (acceptance rate: 20.3%).
Ryo Yoshida,
Yushi Sugimoto,
Yohei Oseki
(2025).
Investigating Psychometric Predictive Power of Syntactic Attention.
Proceedings of the 29th Conference on Computational Natural Language Learning (acceptance rate: 18.4%).
Tatsuki Kuribayashi,
Ryo Ueda,
Ryo Yoshida,
Yohei Oseki,
Ted Briscoe,
Timothy Baldwin
(2024).
Emergent Word Order Universals from Cognitively-Motivated Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (acceptance rate: 21.3%).