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Yusuke Miyao

11 papers hereh-index 475 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6
  • last author3

Across the 9 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CL11
same name
  • Yusuke Miyao — 12 papers, h 42
  • Yusuke Miyao — 9 papers, h 4
  • Yusuke Miyao — 6 papers, h 2
  • Yusuke Miyao — 3 papers, h 2
  • Yusuke Miyao — 2 papers, h 1
  • Yusuke Miyao — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedLLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs

5 citations · 6 across the 9 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CL2026

LLM-jp-4 Technical Report

LLM-jp, :, Chaoran Liu +16

This paper presents LLM-jp-4, a family of Japanese sovereign large language models (LLMs) developed with an emphasis on transparency, reproducibility, and practical usability. LLM-…

cs.CL2026

Measuring Task-Agnostic Training Data Influence Across Language Model Pretraining

Yuto Nishida, Hirokazu Kiyomaru, Yusuke Oda +6

Measuring training data influence consistently across language model pretraining is challenging. It is difficult to select downstream tasks or validation sets representative of a m…

cs.CL2026

Exclusive Unlearning

Mutsumi Sasaki, Kouta Nakayama, Yusuke Miyao +2

When introducing Large Language Models (LLMs) into industrial applications, such as healthcare and education, the risk of generating harmful content becomes a significant challenge…

cs.CL2026★ 1 cited

A Comparative Analysis of LLM Memorization at Statistical and Internal Levels: Cross-Model Commonalities and Model-Specific Signatures

Bowen Chen, Namgi Han, Yusuke Miyao

Memorization is a fundamental component of intelligence for both humans and LLMs. However, while LLM performance scales rapidly, our understanding of memorization lags. Due to limi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.