---
title: "Who cites Unsupervised Learning of — 50 citing papers"
description: "50 papers of the Elamur Research library cite «Unsupervised Learning of Morphology», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/hammarstrom-2011-unsupervised-learning-morphology/cited-by/"
---
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# Who cites «Unsupervised Learning of Morphology»

50 papers of our library cite it (of the 141,840 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Unsupervised Learning of Morphology»](https://md.research.elamur.ai/free/en/papers/hammarstrom-2011-unsupervised-learning-morphology/)

1. [**Semi-supervised learning of morphological paradigms and lexicons**Mans Hulden, Markus Forsberg, Malin Ahlberg*2014 · 188 citations*](https://md.research.elamur.ai/free/en/papers/ahlberg-2014-paradigm-extraction/)
2. [**Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model**Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-chatgpt-wugs-morphology/)
3. [**Morphological Analysis for the Maltese Language: The challenges of a hybrid system**Claudia Borg, Albert Gatt*2017 · 9 citations*](https://md.research.elamur.ai/free/en/papers/borg-2017-morphological-analysis-maltese-language-challenges/)
4. [**Probabilistic Modelling of Morphologically Rich Languages**Jan A. Botha*2015 · 4 citations*](https://md.research.elamur.ai/free/en/papers/botha-2015-probabilistic-modelling-morphologically-rich-languages/)
5. [**Computational Approaches to Arabic-English Code-Switching arXiv:2410.13318**Caroline Sabty*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/sabty-2024-computational-approaches-arabic-english-code/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/hammarstrom-2011-unsupervised-learning-morphology/) — Unsupervised Learning of Morphology