Author

Momose Oyama

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#natural language process... Mar 2026

Language Model Maps for Prompt-Response Distributions via Log-Likelihood Vectors

A method that represents language models by log-likelihood vectors over prompt-response pairs and constructs model maps for comparing their conditional distributions is proposed, which supports the analysis and prediction of input-dependent model behavior.

Yusuke Takase, Momose Oyama, H. Shimodaira · arXiv.org · 0 citations

#natural language process... Mar 2026

Domain Mixture Design via Log-Likelihood Differences for Aligning Language Models with a Target Model

A method for determining domain weights by viewing models as points in log-likelihood space and aligning the training update direction with the direction toward the target model is proposed.

Ryōji Kishino, Riku Shiomi, Hiroaki Yamagiwa et al. · arXiv.org · 0 citations