@inproceedings{berger-2025-transfer,
    title = "Transfer-Learning {German} Metaphors Inspired by Second Language Acquisition",
    author = "Berger, Maria",
    editor = "Johansson, Richard  and
      Stymne, Sara",
    booktitle = "Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library",
    url = "https://preview.aclanthology.org/moar-dois/2025.nodalida-1.6/",
    pages = "48--54",
    ISBN = "978-9908-53-109-0",
    abstract = "A major part of figurative meaning prediction is based on English-language training corpora. One strategy to apply techniques to languages other than English lies in applying transfer learning techniques to correct this imbalance. However, in previous studies we learned that the bilingual representations of current transformer models are incapable of encoding the deep semantic knowledge necessary for a transfer learning step, especially for metaphor prediction. Hence, inspired by second language acquisition, we attempt to improve German metaphor prediction in transfer learning by modifying the context windows of our input samples to align with lower readability indices achieving up to 13{\%} higher F1 score."
}