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Hiroshi Noji

Hiroshi Noji has 2 papers in our library, in 2020–2026, most of them on Vision & language; often with Isao Goto, Jun'ichi Tsujii, Kota Manabe.

2 papers in our library · 2020–2026

OpenAlex · ORCID · h-index 12 · 43 works · 494 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 115 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5642

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 of Advanced Industrial Science and TechnologyTsukuba · Japan2017–2022 · 26 papers🔬Artificial Intelligence Research CenterTokyo · Japan2018–2022 · 13 papers🎓Nara Institute of Science and TechnologyIkoma · Japan2016–2019 · 8 papers🎓The University of TokyoTokyo · Japan2019–2023 · 4 papers🔬National Institute of InformaticsTokyo · Japan2013–2015 · 4 papers🎓Ochanomizu UniversityTokyo · Japan2019 · 2 papers🎓Tokyo Institute of TechnologyTokyo · Japan2019 · 2 papers🎓The Graduate University for Advanced Studies, SOKENDAIHayama · Japan2015 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 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 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Vision & language · 1 work

 Works by year

2020s

20261 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters (2020 · 206 citations)
    Since BERT, most Transformer encoders have kept its wordpiece tokenizer, although the architecture does not require it.
  2. Domain Adaptation of Image Encoder for Multimodal Manga Translation (2026)
    Manga translation systems often struggle because speech-balloon text alone omits subjects and context. Existing multimodal approaches either convert images into tags or captions, or rely on general-purpose image encoders that do not grasp how manga pages are organized. This student-workshop paper proposes adapting a…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From CharactersInternational Conference on Computational Linguistics (COLING)Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.2020 · 206 citations
  2. A* CCG Parsing with a Supertag and Dependency Factored Model ↗Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetMasashi Yoshikawa, Hiroshi Noji, Yuji Matsumoto2017 · 94 citations
  3. Domain Adaptation of Image Encoder for Multimodal Manga TranslationConference of the European Chapter of the Association for Computational Linguistics (EACL)Kota Manabe, Tomoyuki Kajiwara, Takashi Ninomiya, et al.2026

 Co-authors here

8 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 115 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

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