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home / docs / papers / cited-by / Who cites «VARD 2: A tool for dealing with spelling variation in historical corpora»

Who cites «VARD 2: A tool for dealing with spelling variation in historical corpora»

22 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

  1. Analysing LLMs for spelling normalization of 18th century Portuguese — 2026 · Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1
  2. Tracing Syntactic Complexity: Exploring the Evolution of Average Dependency Length Across Three Centuries of Scientific English — our card · 2025 · Proceedings of the Eighth International Conference on Dependency Linguistics (Depling, SyntaxFest 2025)
  3. Tracing Syntactic Change in the Scientific Genre: Two Universal Dependency-parsed Diachronic Corpora of Scientific English and German — our card · 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  4. 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)
  5. 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)
  6. Unsupervised Data Augmentation for Less-Resourced Languages with no Standardized Spelling — 2019 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
  7. Encoder-Decoder Methods for Text Normalization — 2018 · Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018)
  8. Using relative entropy for detection and analysis of periods of diachronic linguistic change — 2018 · Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
  9. Comparing Rule-based and SMT-based Spelling Normalisation for English Historical Texts — our card · 2017 · Proceedings of the NoDaLiDa 2017 Workshop on Processing Historical Language
  10. Improving historical spelling normalization with bi-directional LSTMs and multi-task learning — our card · 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
  11. Information-based Modeling of Diachronic Linguistic Change: from Typicality to Productivity — 2016 · Proceedings of the 10th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities
  12. The Royal Society Corpus: From Uncharted Data to Corpus — 2016 · Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
  13. An open diachronic corpus of historical Spanish: annotation criteria and automatic modernisation of spelling — 2013 · arXiv:1306.3692
  14. Modernizing historical Slovene words with character-based SMT — 2013 · Proceedings of the 4th Biennial International Workshop on Balto-Slavic Natural Language Processing
  15. POS Tagging for Historical Texts with Sparse Training Data — our card · 2013 · Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse
  16. A Gold Standard Corpus of Early Modern German — our card · 2011 · Proceedings of the 5th Linguistic Annotation Workshop
  17. Extending the tool, or how to annotate historical language varieties — 2011 · Proceedings of the 5th ACL-HLT Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities
  18. Annotation and Representation of a Diachronic Corpus of Spanish — 2010 · Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
  19. bizzoni-2021-diffusion-scientific-terms-tracing-individuals
  20. knappen-2017-making-royal-society-corpus
  21. wubben-2013-character-overlap-improve-language-transformation
  22. zimmermann-2019-studying-semantic-chain-shifts-word2vec

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