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Deep Learning-Based Morphological Taggers and Lemmatizers for Annotating Historical Texts.. DATeCH, page 133-137. ACM, (2019)Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages, , , and . Findings of the Association for Computational Linguistics: ACL 2023, page 8320--8340. Toronto, Canada, Association for Computational Linguistics, (July 2023)Werkzeuge zur Extraktion von signifikanten Wortpaaren als Webservice, , , , and . GSCL-Symposium Sprachtechnologie und eHumanities, page 32--43. (2009)Adaptive Bi-nonlinear Neural Networks Based on Complex Numbers with Weights Constrained Along the Unit Circle., , and . PAKDD (1), volume 13935 of Lecture Notes in Computer Science, page 355-366. Springer, (2023)Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages., , , and . ACL (Findings), page 8320-8340. Association for Computational Linguistics, (2023)Probabilistic part-of-speech tagging using decision trees. (1995)GNNavi: Navigating the Information Flow in Large Language Models by Graph Neural Network., , , , and . CoRR, (2024)A Comparative Investigation of Morphological Language Modeling for the Languages of the European Union., , and . HLT-NAACL, page 386-395. The Association for Computational Linguistics, (2012)Why don't people use character-level machine translation?, , and . ACL (Findings), page 2470-2485. Association for Computational Linguistics, (2022)Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding., , , and . KONVENS, page 1-16. Association for Computational Lingustics, (2023)