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Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training.

, , , and . EMNLP (Findings), page 13190-13208. Association for Computational Linguistics, (2023)

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Grammar-driven versus data-driven: which parsing system is more affected by domain shifts?, and . Proceedings of the 2010 Workshop on NLP and Linguistics: Finding the Common Ground, page 25--33. Stroudsburg, PA, USA, Association for Computational Linguistics, (2010)Donkii: Can Annotation Error Detection Methods Find Errors in Instruction-Tuning Datasets?, , , and . CoRR, (2023)What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects., , , and . CoRR, (2024)Team DiSaster at SemEval-2020 Task 11: Combining BERT and Hand-crafted Features for Identifying Propaganda Techniques in News., , and . SemEval@COLING, page 1817-1822. International Committee for Computational Linguistics, (2020)Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat., , , , , , and . NAACL-HLT (1), page 2578-2587. Association for Computational Linguistics, (2019)Robust Cross-Domain Sentiment Analysis for Low-Resource Languages., , and . WASSA@ACL, page 2-7. The Association for Computer Linguistics, (2014)Personality Traits on Twitter - or - How to Get 1, 500 Personality Tests in a Week., and . WASSA@EMNLP, page 92-98. The Association for Computer Linguistics, (2015)An Interdisciplinary Perspective on Evaluation and Experimental Design for Visual Text Analytics: Position Paper., , , , , , , and . BELIV, page 28-37. IEEE, (2022)MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding., and . RepL4NLP@ACL, page 49-54. Association for Computational Linguistics, (2019)Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction., , , , and . NoDaLiDa, page 80-85. University of Tartu Library, (2023)