Author

Yusuke Oda

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#natural language process... Mar 2026

ShapleyLaw: A Game-Theoretic Approach to Multilingual Scaling Laws

This paper considers multilingual pretraining as a cooperative game in which each language acts as a player that jointly contributes to pretraining, gaining the resulting reduction in test loss as the payoff and proposes a game-theoretic multilingual scaling law called ShapleyLaw.

Xuyang Cao, Qian-Ying Liu, Chuan Xiao et al. · arXiv.org · 2 citations

Preprint Aug 2026

Measuring Task-Agnostic Training Data Influence Across Language Model Pretraining

This work proposes a measure of training data influence that does not require selecting a downstream task or validation set as the attribution target, and defines an example's influence by how much its gradient update reduces the squared distance to the final parameters of a given pretraining run.

Yuto Nishida, Hirokazu Kiyomaru, Yusuke Oda et al. · 0 citations