Papers by Steffen Herbold

2 papers
From Isolates to Families: Using Neural Networks for Automated Language Affiliation (2025.acl-long)

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Challenge: linguistic affiliation of languages to a common language family is traditionally carried out manually . large-scale standardized collections of multilingual wordlists and grammatical language structures could improve this .
Approach: They propose to use lexical and grammatical data to classify languages into families using neural network models.
Outcome: The proposed models outperform models trained on lexical and grammatical data while combining both types of data yields even better performance.
Understanding or Memorizing? A Case Study of German Definite Articles in Language Models (2026.acl-long)

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Challenge: grammatical agreement is unclear whether language models rely on memorization or generalization . morphologically rich languages such as German have syncretic forms that are syncretically arranged .
Approach: They use a GRADIEND-based interpretability method to learn parameter update directions for gender-case specific article transitions.
Outcome: Using GRADIEND, we find that updates learned for gender-case specific article transitions affect unrelated gender- case settings .

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