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# Stefan Grünewald

3 paper cards in Mova's library · 2020–2021

Stefan Grünewald wrote 3 of the papers Mova reads, in 2020–2021, most of them on [Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/), [Dependency parsing](https://md.mova.elamur.ai/free/en/docs/papers/topics/dependency-parsing/); often with [Annemarie Friedrich](https://md.mova.elamur.ai/free/en/docs/papers/authors/annemarie-friedrich/), [Jonas Kuhn](https://md.mova.elamur.ai/free/en/docs/papers/authors/jonas-kuhn/), Prisca Piccirilli.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Stefan+Gr%C3%BCnewald) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Stefan+Gr%C3%BCnewald) · [dblp](https://dblp.org/search?q=Stefan+Gr%C3%BCnewald) · [ACL Anthology](https://aclanthology.org/search/?q=Stefan+Gr%C3%BCnewald) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Stefan+Gr%C3%BCnewald)

Topics: [Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/) 3 · [Dependency parsing](https://md.mova.elamur.ai/free/en/docs/papers/topics/dependency-parsing/) 1

## Papers

1. **[Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary](https://md.mova.elamur.ai/free/en/docs/papers/grunewald-2021-applying-occam-s-razor-transformer/)** *(2021)* `measured` Modern graph-based dependency parsers for Universal Dependencies rely on transformer embeddings but differ in several design choices: which pretrained model to use, whether to add LSTM layers, and whether to train jointly on POS and morphology.
2. **[Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling](https://md.mova.elamur.ai/free/en/docs/papers/grunewald-2021-coordinate-constructions-english-enhanced-universal/)** *(2021)* In Enhanced UD, coordination is represented by propagating the first conjunct's relations (its head and its dependents) to the other conjuncts.
3. **[RobertNLP at the IWPT 2020 Shared Task: Surprisingly Simple Enhanced UD Parsing for English](https://md.mova.elamur.ai/free/en/docs/papers/ud-2020-grunewald-robertnlp-iwpt-2020-shared-task/)** *(2020)* RobertNLP builds enhanced UD graphs directly, without a basic tree first. A biaffine classifier over fine-tuned RoBERTa embeddings scores every ordered pair of tokens with a label or with "no relation". Labels that carry words (such as obl:instead_of) are replaced by placeholders, for example obl:[case], which cuts…

## Co-authors (3)

- [Annemarie Friedrich](https://md.mova.elamur.ai/free/en/docs/papers/authors/annemarie-friedrich/) ×3
- [Jonas Kuhn](https://md.mova.elamur.ai/free/en/docs/papers/authors/jonas-kuhn/)
- Prisca Piccirilli
- [← previous Stav Klein](https://md.mova.elamur.ai/free/en/docs/papers/authors/stav-klein/)
- [next → Stefan Müller](https://md.mova.elamur.ai/free/en/docs/papers/authors/stefan-muller/)
- [↑ back to Authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/)