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Shinnosuke Isono

Shinnosuke Isono has 2 papers in our library, in 2026, most of them on Psycholinguistics & language acquisition, Language models & pretraining; often with Ryo Yoshida, Sho Yokoi, Taiga Someya.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 2 · 25 works · 10 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #13131

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🔬National Institute for Japanese Language and LinguisticsTokyo · Japan2025–2026 · 10 paperscurrent🎓The University of TokyoTokyo · Japan2023–2026 · 7 paperscurrent🎓Georgetown UniversityWashington · United States2026 · 3 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksCognitive Neuroscience · 2 worksComputer Science · 2 worksDevelopmental and Educational Psychology · 2 worksLanguage and Linguistics · 2 worksNeuroscience · 2 worksPsychology · 2 works

🧭 Topics 2Research subjects and languages the work is about.Psycholinguistics & language acquisition · 2 worksLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Psycholinguistics · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal (2026 · 1 citation)
    Neural language models (LMs) estimate reading difficulty well on simple, naturalistic text. On garden-path sentences, however, their surprisal predicts far less slowdown than humans actually show. Several researchers have taken this gap as evidence that syntactic disambiguation cost lies outside surprisal theory.…
  2. Timesteps of Mamba Align with Human Reading Times (2026)
    This study asks whether Mamba, a state-space language model, handles words on a time scale that resembles human reading.

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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