collaborators

5 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.CL2025

Generating Completions for Broca's Aphasic Sentences Using Large Language Models

Sijbren van Vaals, Yevgen Matusevych, Frank Tsiwah

Broca's aphasia is a type of aphasia characterized by non-fluent, effortful and agrammatic speech production with relatively good comprehension. Since traditional aphasia treatment…

cs.CL2025

The mutual exclusivity bias of bilingual visually grounded speech models

Dan Oneata, Leanne Nortje, Yevgen Matusevych +1

Mutual exclusivity (ME) is a strategy where a novel word is associated with a novel object rather than a familiar one, facilitating language learning in children. Recent work has f…

cs.CL2025

Child-Directed Language Does Not Consistently Boost Syntax Learning in Language Models

Francesca Padovani, Jaap Jumelet, Yevgen Matusevych +1

Seminal work by Huebner et al. (2021) showed that language models (LMs) trained on English Child-Directed Language (CDL) can reach similar syntactic abilities as LMs trained on muc…