---
title: "Who cites Statistical Methods for Annotation — 16 citing papers"
description: "16 papers of the Elamur Research library cite «Statistical Methods for Annotation Analysis», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/wilkens-2023-statistical-methods-annotation-analysis/cited-by/"
---
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# Who cites «Statistical Methods for Annotation Analysis»

16 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Statistical Methods for Annotation Analysis»](https://md.research.elamur.ai/free/en/papers/wilkens-2023-statistical-methods-annotation-analysis/)

1. **[The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Barbara Plank*2022 · 364 citations*
2. **[ArMIS - The Arabic Misogyny and Sexism Corpus with Annotator Subjective Disagreements](https://md.research.elamur.ai/free/en/papers/almanea-2022-armis-arabic-misogyny-sexism-corpus/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dina Almanea, Massimo Poesio*2022 · 42 citations*
3. **[Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts](https://md.research.elamur.ai/free/en/papers/yu-2023-aggregating-crowdsourced-automatic-judgments-scale/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Juntao Yu, Silviu Paun, Maris Camilleri, et al.*2023 · 12 citations*

13 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/wilkens-2023-statistical-methods-annotation-analysis/) — Statistical Methods for Annotation Analysis