Papers by Stefania Degaetano-Ortlieb

2 papers
Exploring the Effect of Nominal Compound Structure in Scientific Texts on Reading Times of Experts and Novices (2025.acl-srw)

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Challenge: Using a corpus of eye-tracking data of German native speakers, we find that some compound types are associated with longer reading times.
Approach: They use a corpus containing eye-tracking data of german native speakers reading scientific texts.
Outcome: The authors show that some compound types are associated with longer reading times and that experts may have an advantage while reading in-domain texts, but also while reading out-of-domain.
A Closer Look at Linguistic Knowledge in Masked Language Models: The Case of Relative Clauses in American English (2020.coling-main)

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Challenge: Despite the high performance of transformer-based language models, we still lack understanding of the kind of linguistic knowledge they learn and rely on.
Approach: They evaluate three transformer-based language models and test their grammatical and semantic knowledge by sentence-level probing, diagnostic cases, and masked prediction tasks.
Outcome: The models capture grammatical and semantic knowledge, but they lack model-specific weaknesses especially on semantic knowledge.

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