BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop
Lucas Charpentier
Leshem Choshen
Ryan Cotterell
Mustafa Omer Gul
Michael Y. Hu
Jaap Jumelet
Tal Linzen
Jing Liu
Aaron Mueller
Candace Ross
Raj Sanjay Shah
Alex Warstadt
Ethan Gotlieb Wilcox
Adina Williams

Abstract
BabyLM aims to dissolve the boundaries between cognitive modeling and language modeling. We call for both workshop papers and for researchers to join the 3rd BabyLM competition. As in previous years, we call for participants in the data-efficient pretraining challenge in the general track. This year, we also offer a new track: INTERACTION. This new track encourages interactive behavior, learning from a teacher, and adapting the teaching material to the student. We also call for papers outside the competition in any relevant areas. These include training efficiency, cognitively plausible research, weak model evaluation, and more.
View on arXiv@article{charpentier2025_2502.10645, title={ BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop }, author={ Lucas Charpentier and Leshem Choshen and Ryan Cotterell and Mustafa Omer Gul and Michael Hu and Jaap Jumelet and Tal Linzen and Jing Liu and Aaron Mueller and Candace Ross and Raj Sanjay Shah and Alex Warstadt and Ethan Wilcox and Adina Williams }, journal={arXiv preprint arXiv:2502.10645}, year={ 2025 } }
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