Momose Oyama

According to our database, Momose Oyama authored at least 11 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

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

Yusuke Takase, Momose Oyama, Hidetoshi Shimodaira

CoRR, March, 2026

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

Ryo Kishino, Riku Shiomi, Hiroaki Yamagiwa, Momose Oyama, Hidetoshi Shimodaira

CoRR, March, 2026

2025

Revealing Language Model Trajectories via Kullback-Leibler Divergence.

Ryo Kishino, Yusuke Takase, Momose Oyama, Hiroaki Yamagiwa, Hidetoshi Shimodaira

CoRR, May, 2025

Mapping 1,000+ Language Models via the Log-Likelihood Vector.

Momose Oyama, Hiroaki Yamagiwa, Yusuke Takase, Hidetoshi Shimodaira

CoRR, February, 2025

Likelihood Variance as Text Importance for Resampling Texts to Map Language Models.

Momose Oyama, Ryo Kishino, Hiroaki Yamagiwa, Hidetoshi Shimodaira

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings.

Hiroaki Yamagiwa, Momose Oyama, Hidetoshi Shimodaira

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Mapping 1, 000+ Language Models via the Log-Likelihood Vector.

Momose Oyama, Hiroaki Yamagiwa, Yusuke Takase, Hidetoshi Shimodaira

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Predicting Drug-Gene Relations via Analogy Tasks with Word Embeddings.

Hiroaki Yamagiwa, Ryoma Hashimoto, Kiwamu Arakane, Ken Murakami, Shou Soeda, Momose Oyama, Mariko Okada, Hidetoshi Shimodaira

CoRR, 2024

Understanding Higher-Order Correlations Among Semantic Components in Embeddings.

Momose Oyama, Hiroaki Yamagiwa, Hidetoshi Shimodaira

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Discovering Universal Geometry in Embeddings with ICA.

Hiroaki Yamagiwa, Momose Oyama, Hidetoshi Shimodaira

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Norm of Word Embedding Encodes Information Gain.

Momose Oyama, Sho Yokoi, Hidetoshi Shimodaira

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023