--- title: "Ryan Cotterell — papers and cards" description: "Ryan Cotterell: 3 paper cards in the Research library (2017–2023), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/ryan-cotterell/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ryan-cotterell/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ryan Cotterell # Ryan Cotterell 3 paper cards in the Research library · 2017–2023 Ryan Cotterell wrote 3 of the papers Mova reads, in 2017–2023, most of them on [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/); often with Afra Amini, [Chaitanya Malaviya](https://md.research.elamur.ai/free/en/authors/chaitanya-malaviya/), [Christo Kirov](https://md.research.elamur.ai/free/en/authors/christo-kirov/). [OpenAlex](https://openalex.org/A5061951606) · [ORCID](https://orcid.org/0000-0003-4080-1833) · [**h-index 44**](https://openalex.org/authors/A5061951606) · [6252 citations](https://openalex.org/authors/A5061951606) · [425 works](https://openalex.org/works?filter=author.id:A5061951606) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Ryan+Cotterell) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ryan+Cotterell) · [dblp](https://dblp.org/search?q=Ryan+Cotterell) · [ACL Anthology](https://aclanthology.org/search/?q=Ryan+Cotterell) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Ryan+Cotterell) Topics: [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) 1 · [Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) 1 ## Ideas Mova took (1) From the ideas ledger: an idea tried, kept or queued, or measured with no gain, and what it gave. - **measured, no gain** — Tag-conditioned lemma rules in en/src/morph.rs: when the dictionary has several candidates or a suffix rule is ambiguous, choose the rule with the UPOS and FEATS predicted by en/src/ud.rs; measure lemma accuracy on EWT dev, reporting ambiguous tokens (more… *([A Simple Joint Model for Improved Contextual Neural…](https://md.research.elamur.ai/free/en/papers/ud-2019-malaviya-simple-joint-model-improved-contextual/) · lemma by predicted UPOS and relation: EWT dev lemmas 96.67 -> 96.68 (3 tokens); ambiguous forms 97.66% vs the rest 95.67% (split kept in ud-eval EN_UD_DEBUG)…)* ## Papers 1. **[Hexatagging: Projective Dependency Parsing as Tagging](https://md.research.elamur.ai/free/en/papers/acl-2023-amini-hexatagging-projective-dependency-parsing-as/)** *(2023)* The paper turns projective dependency parsing into tagging. Each word receives a "hexatag" from a finite set that encodes the stack actions of a binarized version of its tree, and all words are tagged in parallel with two linear projections over a pretrained encoder. Because validity depends only on the number of… 2. **[A Simple Joint Model for Improved Contextual Neural Lemmatization](https://md.research.elamur.ai/free/en/papers/ud-2019-malaviya-simple-joint-model-improved-contextual/)** *(2019)* Lemmatization maps an inflected form to its citation form, and the right lemma often depends on context, as "running" is a verb in one sentence and a noun in another. 3. **[A Rich Morphological Tagger for English: Exploring the Cross-Linguistic Tradeoff Between Morphology and Syntax](https://md.research.elamur.ai/free/en/papers/kirov-2017-rich-morphological-tagger-english-exploring/)** *(2017)* The question is whether English, a morphologically poor language, carries in its syntax the same meanings that Czech marks with inflection. ## Co-authors (8) - Afra Amini - [Chaitanya Malaviya](https://md.research.elamur.ai/free/en/authors/chaitanya-malaviya/) - [Christo Kirov](https://md.research.elamur.ai/free/en/authors/christo-kirov/) - [John Sylak-Glassman](https://md.research.elamur.ai/free/en/authors/john-sylak-glassman/) - [Matt Post](https://md.research.elamur.ai/free/en/authors/matt-post/) - Rebecca Knowles - Shijie Wu - Tianyu Liu ## More papers in the library (5) Pages of the Research library: our summary, the ideas, references and who cites each. - [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/) — Yuchen Jiang, Tianyu Liu, Shuming Ma, et al. · 2022 - [Information-Theoretic Probing for Linguistic Structure](https://md.research.elamur.ai/free/en/papers/pimentel-2020-information-theoretic-probing-linguistic-structure/) — Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay, et al. · 2020 - [Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://md.research.elamur.ai/free/en/papers/zmigrod-2019-counterfactual-data-augmentation-mitigating-gender/) — Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al. · 2019 - [Gender Bias in Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2019-gender-bias-contextualized-word-embeddings/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · 2019 - [Marrying Universal Dependencies and Universal Morphology](https://md.research.elamur.ai/free/en/papers/mccarthy-2018-marrying-universal-dependencies-universal-morphology/) — Arya D. McCarthy, Miikka Silfverberg, Ryan Cotterell, et al. · 2018