Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding

Hidetaka Kamigaito, Hiroyuki Deguchi, Yusuke Sakai, Katsuhiko Hayashi, Taro Watanabe. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

Authors

Katsuhiko Hayashi (ORCID: https://orcid.org/0000-0002-2479-2941)
Hidetaka Kamigaito (ORCID: https://orcid.org/0000-0002-5249-5813)
Yusuke Sakai (ORCID: https://orcid.org/0000-0001-8810-4813)
Hiroyuki Deguchi (ORCID: https://orcid.org/0000-0003-2127-6607)
Taro Watanabe

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.18653/v1/2025.acl-long.1410
Citations: 1
Primary Topic: Law, Economics, and Judicial Systems
Type: article
Field-Weighted Citation Impact: 3.13

Funders

Japan Society for the Promotion of Science

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article

Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding

Katsuhiko Hayashi, Hidetaka Kamigaito, Yusuke Sakai, Hiroyuki Deguchi et al.

Jan 1, 2025

1 citations

Law, Economics, and Judicial Systems

3.13

article

Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding

Katsuhiko Hayashi, Hidetaka Kamigaito, Yusuke Sakai, Hiroyuki Deguchi, Taro Watanabe

January 1, 2025article en

1 citations

Abstract

Japan Society for the Promotion of Science

Climate action

Openalex Percentile: Top 7%

Law, Economics, and Judicial Systems

3.13

DOI Open Access PDF OpenAlex

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Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding — Katsuhiko Hayashi, Hidetaka Kamigaito, et al. · (2025) | TGRS Research Map | TGRS