Overlapping Context with Variable-Length Stride Increases Diversity when Training Large Language Model for Code

Geonmo Gu, Jaeho Kwak, Haksoo Moon, Hyun Seung Shim, Yu Jin Kim, Byoungjip Kim, Moontae Lee, Hyejeong Jeon. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track). 2025.

Authors

Yu Jin Kim
Hongyoung Jeon (ORCID: https://orcid.org/0000-0003-4541-0655)
Byoungjip Kim
J.G. Kwak (ORCID: https://orcid.org/0000-0002-4886-3193)
Hyungbo Shim (ORCID: https://orcid.org/0000-0002-5972-8114)
Moontae Lee (ORCID: https://orcid.org/0000-0001-5542-3463)
Geonmo Gu
H. P. Moon

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.18653/v1/2025.acl-industry.32
Primary Topic: Natural Language Processing Techniques
Type: article
Field-Weighted Citation Impact: 0.00

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article

Overlapping Context with Variable-Length Stride Increases Diversity when Training Large Language Model for Code

Yu Jin Kim, Hongyoung Jeon, Byoungjip Kim, J.G. Kwak et al.

Jan 1, 2025

Natural Language Processing Techniques

article

Overlapping Context with Variable-Length Stride Increases Diversity when Training Large Language Model for Code

Yu Jin Kim, Hongyoung Jeon, Byoungjip Kim, J.G. Kwak, Hyungbo Shim, Moontae Lee, Geonmo Gu, H. P. Moon

January 1, 2025article en

Abstract

Quality Education

Openalex Percentile: Top 90%

Natural Language Processing Techniques

DOI Open Access PDF OpenAlex

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Overlapping Context with Variable-Length Stride Increases Diversity when Training Large Language Model for Code — Yu Jin Kim, Hongyoung Jeon, et al. · (2025) | TGRS Research Map | TGRS