24 citations · 63 across the 44 of their papers we have counts for
5 papers · 1 filter
Do Syntactic Categories Help in Developmentally Motivated Curriculum Learning for Language Models?
Arzu Burcu Güven, Anna Rogers, Rob van der Goot
We examine the syntactic properties of BabyLM corpus, and age-groups within CHILDES. While we find that CHILDES does not exhibit strong syntactic differentiation by age, we show th…
Crossing Domains without Labels: Distant Supervision for Term Extraction
Elena Senger, Yuri Campbell, Rob van der Goot +1
Automatic Term Extraction (ATE) is a critical component in downstream NLP tasks such as document tagging, ontology construction and patent analysis. Current state-of-the-art method…
NLPnorth @ TalentCLEF 2025: Comparing Discriminative, Contrastive, and Prompt-Based Methods for Job Title and Skill Matching
Mike Zhang, Rob van der Goot
Matching job titles is a highly relevant task in the computational job market domain, as it improves e.g., automatic candidate matching, career path prediction, and job market anal…
DaKultur: Evaluating the Cultural Awareness of Language Models for Danish with Native Speakers
Max Müller-Eberstein, Mike Zhang, Elisa Bassignana +2
Large Language Models (LLMs) have seen widespread societal adoption. However, while they are able to interact with users in languages beyond English, they have been shown to lack c…
From Smør-re-brød to Subwords: Training LLMs on Danish, One Morpheme at a Time
Mikkel Wildner Kildeberg, Emil Allerslev Schledermann, Nicolaj Larsen +1
The best performing transformer-based language models use subword tokenization techniques, such as Byte-Pair-Encoding (BPE). However, these approaches often overlook linguistic pri…