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20182026
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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

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…

cs.CL2025

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.CL2025

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…

cs.CL2024

Interpretability of Language Models via Task Spaces

Lucas Weber, Jaap Jumelet, Elia Bruni +1

The usual way to interpret language models (LMs) is to test their performance on different benchmarks and subsequently infer their internal processes. In this paper, we present an…

cs.CL2024

Do Language Models Exhibit Human-like Structural Priming Effects?

Jaap Jumelet, Willem Zuidema, Arabella Sinclair

We explore which linguistic factors -- at the sentence and token level -- play an important role in influencing language model predictions, and investigate whether these are reflec…