4 citations · 5 across the 8 of their papers we have counts for
8 papers
Probing Factual Knowledge Transfer with Training Data Interventions
Romina Oji, Marc Braun, Marcel Bollmann +2
Do multilingual language models transfer factual knowledge across languages during continued pretraining, or do they mostly recall facts learned directly from the target-language d…
Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training
Lukas Borggren, Jenny Kunz, Marco Kuhlmann
Large language models are increasingly capable in general, but their utility can remain modest in niche or understudied areas. One approach to address this limitation is to special…
A Dataset for Probing Translationese Preferences in English-to-Swedish Translation
Jenny Kunz, Anja Jarochenko, Marcel Bollmann
Translations often carry traces of the source language, a phenomenon known as translationese. We introduce the first freely available English-to-Swedish dataset contrasting transla…
Preferences for Idiomatic Language are Acquired Slowly -- and Forgotten Quickly: A Case Study on Swedish
Jenny Kunz
In this study, we investigate how language models develop preferences for \textit{idiomatic} as compared to \textit{linguistically acceptable} Swedish, both during pretraining and…
Dialects of Translationese Shape Language Model Learning
Jenny Kunz
Machine-translated data is widely used in multilingual NLP, particularly where native text is scarce. However, translated text differs systematically from native text. This phenome…
Grow Up and Merge: Scaling Strategies for Efficient Language Adaptation
Kevin Glocker, Kätriin Kukk, Romina Oji +3
Achieving high-performing language models which include medium- and lower-resource languages remains a challenge. Massively multilingual models still underperform compared to langu…
Properties and Challenges of LLM-Generated Explanations
Jenny Kunz, Marco Kuhlmann
The self-rationalising capabilities of large language models (LLMs) have been explored in restricted settings, using task/specific data sets. However, current LLMs do not (only) re…
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising Models
Marc Braun, Jenny Kunz
The self-rationalising capabilities of LLMs are appealing because the generated explanations can give insights into the plausibility of the predictions. However, how faithful the e…