565 citations · 565 across the 11 of their papers we have counts for
12 papers
Assessing the Impact of Language Disparity on Multilingual Linguistic Ability in Large Language Models
Zhanyu Chen, Jaap Jumelet
Claims about the grammatical competence of multilingual language models vary sharply with how competence is measured, yet the interaction between evaluation paradigm, post-training…
CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions
Francesca Padovani, Xiulin Yang, Bastian Bunzeck +4
CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Leveraging the recent release of t…
Is Child-Directed Language Optimized for Word Learning? A Computational Study of Verb Meaning Acquisition
Francesca Padovani, Jaap Jumelet, Yevgen Matusevych +1
Is child-directed language (CDL) optimized to support language learning, and which aspects of linguistic development does it facilitate? We investigate this question using neural l…
Vocabulary shapes cross-lingual variation of word-order learnability in language models
Jonas Mayer Martins, Jaap Jumelet, Viola Priesemann +1
Why do some languages like Czech permit free word order, while others like English do not? We address this question by pretraining transformer language models on a spectrum of synt…
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…
Propositional Logic for Probing Generalization in Neural Networks
Anna Langedijk, Jaap Jumelet, Willem Zuidema
The extent to which neural networks are able to acquire and represent symbolic rules remains a key topic of research and debate. Much current work focuses on the impressive capabil…
TurBLiMP: A Turkish Benchmark of Linguistic Minimal Pairs
Ezgi Başar, Francesca Padovani, Jaap Jumelet +1
We introduce TurBLiMP, the first Turkish benchmark of linguistic minimal pairs, designed to evaluate the linguistic abilities of monolingual and multilingual language models (LMs).…
Finding Structure in Language Models
Jaap Jumelet
When we speak, write or listen, we continuously make predictions based on our knowledge of a language's grammar. Remarkably, children acquire this grammatical knowledge within just…
Black Big Boxes: Tracing Adjective Order Preferences in Large Language Models
Jaap Jumelet, Lisa Bylinina, Willem Zuidema +1
In English and other languages, multiple adjectives in noun phrases follow intricate ordering patterns. These patterns have been widely studied in linguistics and provide a useful…
ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation
Jaap Jumelet, Michael Hanna, Marianne de Heer Kloots +3
We present the submission of the ILLC at the University of Amsterdam to the BabyLM challenge (Warstadt et al., 2023), in the strict-small track. Our final model, ChapGTP, is a mask…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…