collaborators

11 papers

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs

Jaap Jumelet, Leonie Weissweiler, Joakim Nivre +1

We introduce MultiBLiMP 1.0, a massively multilingual benchmark of linguistic minimal pairs, covering 101 languages and 2 types of subject-verb agreement, containing more than 128,…

cs.CL2026

A Unified Assessment of the Poverty of the Stimulus Argument for Neural Language Models

Xiulin Yang, Arianna Bisazza, Nathan Schneider +1

Several recent contributions have evaluated the Poverty of the Stimulus Hypothesis (PoSH) using Artificial Neural Networks (ANNs). The results suggest that ANN-based language model…

cs.CL2026

Assessing the Impact of Typological Features on Multilingual Machine Translation in the Age of Large Language Models

Vitalii Hirak, Jaap Jumelet, Arianna Bisazza

Despite major advances in multilingual modeling, large quality disparities persist across languages. Besides the obvious impact of uneven training resources, typological properties…

cs.CL2025

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).…