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LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish.

, , , , , , , , и . LREC, стр. 5080-5089. European Language Resources Association, (2022)

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Cédric Bodet

Cédric Müller

Cédric Allène

Cedric Walravens

Cedric Raguenaud

 

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Evaluating Pretrained Transformer-based Models on the Task of Fine-Grained Named Entity Recognition., , , , и . COLING, стр. 3750-3760. International Committee on Computational Linguistics, (2020)Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling., , , , , и . NLDB, том 12801 из Lecture Notes in Computer Science, стр. 367-375. Springer, (2021)Evaluating Parameter-Efficient Finetuning Approaches for Pre-trained Models on the Financial Domain., , , , , и . EMNLP (Findings), стр. 15482-15491. Association for Computational Linguistics, (2023)Evaluating Data Augmentation Techniques for the Training of Luxembourgish Language Models., , , и . KONVENS, стр. 174-179. Association for Computational Lingustics, (2023)Evaluating the Impact of Text De-Identification on Downstream NLP Tasks., , , , , , , , и . NoDaLiDa, стр. 10-16. University of Tartu Library, (2023)LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish., , , , , , , , и . LREC, стр. 5080-5089. European Language Resources Association, (2022)A Comparison of Pre-Trained Language Models for Multi-Class Text Classification in the Financial Domain., , , , , , и . WWW (Companion Volume), стр. 260-268. ACM / IW3C2, (2021)Comparing Pre-Training Schemes for Luxembourgish BERT Models., , , , , , , , и . KONVENS, стр. 17-27. Association for Computational Lingustics, (2023)Revisiting Code Similarity Evaluation with Abstract Syntax Tree Edit Distance., , , , и . CoRR, (2024)Enhancing Text-to-SQL Translation for Financial System Design., , , , , , , , и . ICSE-SEIP, стр. 252-262. ACM, (2024)