BabyLM 4 at EMNLP 2026
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Description
BabyLM returns for its 4th year as both a shared task and a workshop at EMNLP 2026. This round keeps the core goal: sample-efficient pretraining under human-scale data budgets, while updating the track structure and datasets.
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Meet the speakers
L
Leshem Choshen
Theme:IBM Research, MIT
R
Ryan Cotterell
Theme:ETH Zurich
M
Mustafa Omer Gul
Theme:Cornell University
J
Jaap Jumelet
Theme:University of Groningen
T
Tal Linzen
Theme:NYU
A
Aaron Mueller
Theme:Boston University
S
Suchir Salhan
Theme:University of Cambridge
R
Raj Sanjay Shah
Theme:Georgia Institute of Technology
A
Alex Warstadt
Theme:UCSD
E
Ethan Wilcox
Theme:Georgetown
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