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Exploiting Prototypical Explanations for Undersampling Imbalanced Datasets., , , , , и . ICMLA, стр. 1449-1454. IEEE, (2022)Comparing Pre-Training Schemes for Luxembourgish BERT Models., , , , , , , , и . KONVENS, стр. 17-27. Association for Computational Lingustics, (2023)Letz Translate: Low-Resource Machine Translation for Luxembourgish., , , , , и . CoRR, (2023)Rethinking the Event Coding Pipeline with Prompt Entailment., и . CoRR, (2022)Towards Refined Classifications Driven by SHAP Explanations., , , , , , , , и . CD-MAKE, том 13480 из Lecture Notes in Computer Science, стр. 68-81. Springer, (2022)LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish., , , , , , , , и . LREC, стр. 5080-5089. European Language Resources Association, (2022)On the Suitability of SHAP Explanations for Refining Classifications., , , , , , , , и . ICAART (3), стр. 395-402. SCITEPRESS, (2022)Evaluating the Impact of Text De-Identification on Downstream NLP Tasks., , , , , , , , и . NoDaLiDa, стр. 10-16. University of Tartu Library, (2023)