Fabian David Schmidt

Fabian David Schmidt

PhD focusing on Cross-Lingual NLP at University of Würzburg

Publications

SLICER: Sliced Fine-Tuning for Low-Resource Cross-Lingual Transfer for Named Entity Recognition

Published in In the proceedings of Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

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Recommended citation: Fabian Schmidt, Ivan Vuli{\'c}, Goran Glava{\v{s}}, "SLICER: Sliced Fine-Tuning for Low-Resource Cross-Lingual Transfer for Named Entity Recognition." In the proceedings of Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022. https://aclanthology.org/2022.emnlp-main.740

Don't Stop Fine-Tuning: On Training Regimes for Few-Shot Cross-Lingual Transfer with Multilingual Language Models

Published in In the proceedings of Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

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Recommended citation: Fabian Schmidt, Ivan Vuli{\'c}, Goran Glava{\v{s}}, "Don't Stop Fine-Tuning: On Training Regimes for Few-Shot Cross-Lingual Transfer with Multilingual Language Models." In the proceedings of Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022. https://aclanthology.org/2022.emnlp-main.736

SEAGLE: A Platform for Comparative Evaluation of Semantic Encoders for Information Retrieval

Published in In the proceedings of Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, 2019

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Recommended citation: Fabian Schmidt, Markus Dietsche, Simone Ponzetto, Goran Glava{\v{s}}, "SEAGLE: A Platform for Comparative Evaluation of Semantic Encoders for Information Retrieval." In the proceedings of Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, 2019. https://aclanthology.org/D19-3034