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Haruki Sakajo

Haruki Sakajo has 2 papers in our library, in 2026, most of them on Low-resource languages, Language models & pretraining, Vision & language; often with Arturo Martínez Peguero, Frederikus Hudi, Justin Vasselli.

2 papers in our library · 2026

OpenAlex · h-index 1 · 16 works · 3 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 2 times in our library · ⭐ Paper Stars ranking: #12500

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

🎓Nara Institute of Science and TechnologyIkoma · Japan2025–2026 · 14 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Low-resource languages · 2 worksLanguage models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Measuring Linguistic Competence of LLMs on Indigenous Languages of the Americas (2026 · 1 citation)
    The paper asks how much LLMs actually know about Indigenous languages of the Americas. Existing benchmarks mostly cover high-resource languages or focus narrowly on machine translation. The authors build a prompting-only probing benchmark, with no fine-tuning, from AmericasNLP 2025 Shared Task development data…
  2. Nearest-Neighbor Retrieval for Indigenous Image Captioning (2026 · 1 citation)
    This NAIST paper presents the team's entry for the AmericasNLP 2026 shared task, which focuses on generating image captions in Indigenous languages. The task covers Bribri, Guaraní, Nahuatl, Wixárika, and Yucatec Maya, all of which have very little training data. The authors compare two systems.

 Co-authors here

4 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 2 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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