A Joint Matrix Factorization Analysis of Multilingual Representations

Zheng Zhao, Yftah Ziser, Bonnie L. Webber, Shay B Cohen

Submission Type: Regular Long Paper

Submission Track: Multilinguality and Linguistic Diversity

Submission Track 2: Language Modeling and Analysis of Language Models

Keywords: Representation analysis, Multilingual pre-trained models, Matrix factorization, Morphosyntactic features

TL;DR: We present an analysis tool based on joint matrix factorization for comparing latent representations of multilingual and monolingual models.

Abstract:

We present an analysis tool based on joint matrix factorization for comparing latent representations of multilingual and monolingual models. An alternative to probing, this tool allows us to analyze multiple sets of representations in a joint manner. Using this tool, we study to what extent and how morphosyntactic features are reflected in the representations learned by multilingual pre-trained models. We conduct a large-scale empirical study of over 33 languages and 17 morphosyntactic categories. Our findings demonstrate variations in the encoding of morphosyntactic information across upper and lower layers, with category-specific differences influenced by language properties. Hierarchical clustering of the factorization outputs yields a tree structure that is related to phylogenetic trees manually crafted by linguists. Moreover, we find the factorization outputs exhibit strong associations with performance observed across different cross-lingual tasks.
We release our code to facilitate future research.

Submission Number: 1162