arxiv:2510.10159

BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data

Published on Oct 11, 2025

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Authors:

Bastian Bunzeck ,

Julen Etxaniz ,

Linyang He ,

María Grandury ,

Nikitas Theodoropoulos ,

Suchir Salhan ,

Abstract

BabyBabelLM is a multilingual dataset collection for modeling language acquisition from birth, facilitating multilingual pretraining and cognitive modeling.

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We present BabyBabelLM, a multilingual collection of datasets modeling the language a person observes from birth until they acquire a native language. We curate developmentally plausible pretraining data aiming to cover the equivalent of 100M English words of content in each of 45 languages. We compile evaluation suites and train baseline models in each language. BabyBabelLM aims to facilitate multilingual pretraining and cognitive modeling.

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