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# Who cites «Multi-task learning for historical text normalization: Size matters»

9 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2018-bollmann-multi-task-learning-historical-text/)

1. [Multilingual Event Extraction from Historical Newspaper Adverts](https://aclanthology.org/2023.acl-long.574/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD](https://aclanthology.org/2021.findings-acl.305/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
3. [Semi-supervised Contextual Historical Text Normalization](https://md.mova.elamur.ai/free/en/docs/papers/acl-2020-makarov-semi-supervised-contextual-historical-text/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
4. [When is Multi-task Learning Beneficial for Low-Resource Noisy Code-switched User-generated Algerian Texts?](https://aclanthology.org/2020.calcs-1.3/) *— 2020 · Proceedings of the 4th Workshop on Computational Approaches to Code Switching*
5. [A Large-Scale Comparison of Historical Text Normalization Systems](https://md.mova.elamur.ai/free/en/docs/papers/bollmann-2019-large-scale-comparison-historical-text/) *— our card · 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)*
6. [A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations](https://aclanthology.org/N19-1254/) *— 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)*
7. [Controllable Paraphrase Generation with a Syntactic Exemplar](https://aclanthology.org/P19-1599/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
8. [Few-Shot and Zero-Shot Learning for Historical Text Normalization](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2019-bollmann-few-shot-zero-shot-learning/) *— our card · 2019 · Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)*
9. [Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set](https://aclanthology.org/D19-1329/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
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