Year: 2025
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Jumelet, Jaap, Fourtassi, Abdellah, Haga, Akari, Bunzeck, Bastian, Shandilya, Bhargav, Galvan-Sosa, Diana, Haznitrama, Faiz Ghifari, Padovani, Francesca, Meyer, Francois, Hu, Hai, Etxaniz, Julen, Prévot, Laurent, He, Linyang, Grandury, María, Marcheva, Mila, Foroutan, Negar, Theodoropoulos, Nikitas, Sadeghi, Pouya, Song, Siyuan, Salhan, Suchir, Zhou, Susana, Paniv, Yurii, Zhang, Ziyin, Bisazza, Arianna, Warstadt, Alex, Choshen, Leshem
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7091187395
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