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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

  1. Multilingual Event Extraction from Historical Newspaper Adverts — 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 — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  3. Semi-supervised Contextual Historical Text Normalization — 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? — 2020 · Proceedings of the 4th Workshop on Computational Approaches to Code Switching
  5. A Large-Scale Comparison of Historical Text Normalization Systems — 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 — 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 — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  8. Few-Shot and Zero-Shot Learning for Historical Text Normalization — 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 — 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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