--- title: "Who cites POS Tagging for Historical Texts with Sparse…" description: "9 papers of the Elamur Research library cite «POS Tagging for Historical Texts with Sparse Training Data», found in their bibliographies; the most cited…" canonical: "https://research.elamur.ai/free/en/papers/bollmann-2013-pos-tagging-historical-texts-sparse/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/bollmann-2013-pos-tagging-historical-texts-sparse/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [POS Tagging for Historical Texts with Sparse…](https://md.research.elamur.ai/free/en/papers/bollmann-2013-pos-tagging-historical-texts-sparse/) / cited by # Who cites «POS Tagging for Historical Texts with Sparse Training Data» 9 papers of our library cite it (of the 140,884 whose bibliographies we read) · 3 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/bollmann-2013-pos-tagging-historical-texts-sparse/) 1. [**Diachronic proximity vs. data sparsity in cross-lingual parser projection. A case study on Germanic**Maria Sukhareva, Christian Chiarcos*2014 · 12 citations*](https://md.research.elamur.ai/free/en/papers/sukhareva-2014-diachronic-proximity-vs-data-sparsity/) 2. [**Normalizing without Modernizing: Keeping Historical Wordforms of Middle French while Reducing Spelling Variants**Raphael Rubino, Johanna Gerlach, Jonathan Mutal, et al.*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/rubino-2024-normalizing-without-modernizing-keeping-historical/) 3. [**Whit's the Richt Pairt o Speech: PoS tagging for Scots**Harm Lameris, Sara Stymne*2021 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lameris-2021-whit-s-richt-pairt-o/) 6 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/bollmann-2013-pos-tagging-historical-texts-sparse/) — POS Tagging for Historical Texts with Sparse Training Data