3 citations · 3 across the 6 of their papers we have counts for
9 papers · 1 filter
Dual Alignment Between Language Model Layers and Human Sentence Processing
Tatsuki Kuribayashi, Alex Warstadt, Yohei Oseki +1
A recent study (Kuribayashi et al., 2025) has shown that human sentence processing behavior, typically measured on syntactically unchallenging constructions, can be effectively mod…
BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop
Leshem Choshen, Ryan Cotterell, Mustafa Omer Gul +7
The goal of the BabyLM is to stimulate new research connections between cognitive modeling and language model pretraining. We invite contributions in this vein to the BabyLM Worksh…
BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data
Jaap Jumelet, Abdellah Fourtassi, Akari Haga +23
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 pla…
The Harmonic Structure of Information Contours
Eleftheria Tsipidi, Samuel Kiegeland, Franz Nowak +5
The uniform information density (UID) hypothesis proposes that speakers aim to distribute information evenly throughout a text, balancing production effort and listener comprehensi…
Towards Developmentally Plausible Rewards: Communicative Success as a Learning Signal for Interactive Language Models
Lennart Stöpler, Rufat Asadli, Mitja Nikolaus +2
We propose a method for training language models in an interactive setting inspired by child language acquisition. In our setting, a speaker attempts to communicate some informatio…
BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop
Lucas Charpentier, Leshem Choshen, Ryan Cotterell +11
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…