--- title: "Yasuhisa Fujii — author profile and papers — Elamur Research" description: "Yasuhisa Fujii: 2 papers on Elamur Research (2023–2024) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yasuhisa-fujii/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yasuhisa-fujii/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yasuhisa Fujii # Yasuhisa Fujii Yasuhisa Fujii has 2 papers in our library, in 2023–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Chen-Yu Lee](https://md.research.elamur.ai/free/en/authors/chen-yu-lee/), [Chun-Liang Li](https://md.research.elamur.ai/free/en/authors/chun-liang-li/), [Tomas Pfister](https://md.research.elamur.ai/free/en/authors/tomas-pfister/). 2 papers in our library · 2023–2024 No OpenAlex profile matched yet. [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/#papers) · [🔗 Cited 477 times in our library](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/cited-by/) · [⭐ Paper Stars ranking: #3157](https://md.research.elamur.ai/free/en/paper-stars/page/32/#star-3157) 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=Yasuhisa+Fujii) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yasuhisa+Fujii) · [dblp](https://dblp.org/search?q=Yasuhisa+Fujii) · [ACL Anthology](https://aclanthology.org/search/?q=Yasuhisa+Fujii) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 6 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/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [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/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)** *(2023 · 690 citations)* Small task-specific models are cheap to serve, but they usually need many human labels (finetuning) or large pools of unlabeled data (distillation from an LLM) to approach LLM quality. 2. **[Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-chain-table-evolving-tables-reasoning/)** *(2024 · 105 citations)* Large language models can answer questions about tables and check claims against them. However, common reasoning methods record intermediate steps either as plain text (Chain-of-Thought) or as one generated program such as SQL. Both approaches struggle with messy tables, for example when a single cell combines a name… ## Co-authors here 12 of 14 co-authors with a page, the most papers together first. - [Chen-Yu Lee](https://md.research.elamur.ai/free/en/authors/chen-yu-lee/) ×2 - [Chun-Liang Li](https://md.research.elamur.ai/free/en/authors/chun-liang-li/) ×2 - [Tomas Pfister](https://md.research.elamur.ai/free/en/authors/tomas-pfister/) ×2 - [Alexander Ratner](https://md.research.elamur.ai/free/en/authors/alexander-ratner/) - [Cheng-Yu Hsieh](https://md.research.elamur.ai/free/en/authors/cheng-yu-hsieh/) - [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/) - [Hootan Nakhost](https://md.research.elamur.ai/free/en/authors/hootan-nakhost/) - [Jingbo Shang](https://md.research.elamur.ai/free/en/authors/jingbo-shang/) - [Julian Eisenschlos](https://md.research.elamur.ai/free/en/authors/julian-eisenschlos/) - [Lesly Miculicich](https://md.research.elamur.ai/free/en/authors/lesly-miculicich/) - [Ranjay Krishna](https://md.research.elamur.ai/free/en/authors/ranjay-krishna/) - [Vincent Perot](https://md.research.elamur.ai/free/en/authors/vincent-perot/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2023](https://md.research.elamur.ai/free/en/venues/findings/2023/) ## Cited by Papers of our library cite their works 477 times (of the 149,439 papers whose bibliographies we read); [107 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yasuhisa-fujii/cited-by/). Updated 2 November 2026