--- title: "Shohei Taniguchi — author profile and papers in our library" description: "Shohei Taniguchi, The University of Tokyo: 2 papers on Elamur Research (2026), h-index 10 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/shohei-taniguchi/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/shohei-taniguchi/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Shohei Taniguchi # Shohei Taniguchi Shohei Taniguchi has 2 papers in our library, in 2026; often with [Yutaka Matsuo](https://md.research.elamur.ai/free/en/authors/yutaka-matsuo/), [Takeshi Kojima](https://md.research.elamur.ai/free/en/authors/takeshi-kojima/), [Yusuke Iwasawa](https://md.research.elamur.ai/free/en/authors/yusuke-iwasawa/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5112922134) · [**h-index 10**](https://openalex.org/authors/A5112922134) · [46 works](https://openalex.org/works?filter=author.id:A5112922134) · [241 citations](https://openalex.org/works?filter=author.id:A5112922134&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/shohei-taniguchi/#papers) · [⭐ Paper Stars ranking: #13909](https://md.research.elamur.ai/free/en/paper-stars/page/140/#star-13909) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Shohei+Taniguchi) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shohei+Taniguchi) · [dblp](https://dblp.org/search?q=Shohei+Taniguchi) · [ACL Anthology](https://aclanthology.org/search/?q=Shohei+Taniguchi) ## Affiliations [🎓**The University of Tokyo** Tokyo · Japan 2020–2026 · 16 papers*current*](https://md.research.elamur.ai/free/en/universities/the-university-of-tokyo/) · [🏢**Panasonic** Kadoma · Japan 2009–2024 · 5 papers](https://ror.org/011tm7n37) · [🎓**Hokkaido University** Sapporo · Japan 2014–2021 · 5 papers](https://md.research.elamur.ai/free/en/universities/hokkaido-university/) · [🔬**Tokyo Metropolitan Industrial Technology Research Institute** Tokyo · Japan 2001–2008 · 4 papers](https://ror.org/05sa4da38) · [🏢**Panasonic Electric Works Co., Ltd.** Kadoma · Japan 2009–2011 · 2 papers](https://ror.org/03mc0fa98) 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 5 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/shohei-taniguchi/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Infinity-MoE: Generalizing Mixture of Experts to Infinite Experts](https://md.research.elamur.ai/free/en/papers/takashiro-2026-infinity-moe-generalizing-mixture-experts/)** *(2026)* Mixture of Experts (MoE) layers grow model capacity without a matching rise in per-token compute. However, the experts are independent, discrete units, which makes training harder as their number increases. The authors propose ∞-MoE, which replaces the discrete expert set with a continuous expert space. For each… 2. **[Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers](https://md.research.elamur.ai/free/en/papers/shimizu-2026-position-encoding-random-float-sampling/)** *(2026)* Transformers often fail on inputs longer than their training context. Standard integer position indices beyond the trained range are out-of-distribution (OOD), and training on longer sequences is expensive. The authors propose Random Float Sampling (RFS), a position indexing scheme that needs no fine-tuning. During… ## Co-authors here 3 co-authors with a page, the most papers together first. - [Yutaka Matsuo](https://md.research.elamur.ai/free/en/authors/yutaka-matsuo/) ×2 - [Takeshi Kojima](https://md.research.elamur.ai/free/en/authors/takeshi-kojima/) - [Yusuke Iwasawa](https://md.research.elamur.ai/free/en/authors/yusuke-iwasawa/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) Updated 1 November 2026