---
title: "Carlos Gómez-Rodríguez — author profile and papers"
description: "Carlos Gómez-Rodríguez: 11 papers on Elamur Research (2010–2026) — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/"
---
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# Carlos Gómez-Rodríguez

Carlos Gómez-Rodríguez has 11 papers in our library, in 2010–2026, most of them on [Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/), [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/), [English](https://md.research.elamur.ai/free/en/topics/english/); often with [Mark Anderson](https://md.research.elamur.ai/free/en/authors/mark-anderson/), [David Vilares](https://md.research.elamur.ai/free/en/authors/david-vilares/), [Joakim Nivre](https://md.research.elamur.ai/free/en/authors/joakim-nivre/). 4 of them are among the papers read by [Mova, the project](https://md.research.elamur.ai/free/en/projects/mova/).

11 papers in our library · 2010–2026

No OpenAlex profile matched yet.

[📄 11 works in our library](https://md.research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/#papers) · [🔗 Cited 130 times in our library](https://md.research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/cited-by/) · [⭐ Paper Stars ranking: #4301](https://md.research.elamur.ai/free/en/paper-stars/page/44/#star-4301)

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=Carlos+G%C3%B3mez-Rodr%C3%ADguez) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Carlos+G%C3%B3mez-Rodr%C3%ADguez) · [dblp](https://dblp.org/search?q=Carlos+G%C3%B3mez-Rodr%C3%ADguez) · [ACL Anthology](https://aclanthology.org/search/?q=Carlos+G%C3%B3mez-Rodr%C3%ADguez)

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 11 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 11 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 11 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 11 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/)

🧭 Topics 9 Research subjects and languages the work is about.[Dependency parsing · 4 works](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [English · 3 works](https://md.research.elamur.ai/free/en/topics/english/) · [Universal Dependencies · 4 works](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Low-resource languages · 2 works](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Part-of-speech tagging · 1 work](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) · [Syntax & grammar formalisms · 1 work](https://md.research.elamur.ai/free/en/topics/syntax-grammar/)

💡 Concepts 1 Key ideas and methods explained on our concept pages.[Context-free grammar · 1 work](https://md.research.elamur.ai/free/en/concepts/context-free-grammar/)

## Works by year

### 2020s

[**2026** 1 paper Carlos Gómez-Rodríguez's papers of 2026](https://md.research.elamur.ai/free/en/papers/roca-2026-sequence-labeling-constituent-parsing-comparative/) · [**2025** 1 paper Carlos Gómez-Rodríguez's papers of 2025](https://md.research.elamur.ai/free/en/papers/kellert-2025-parsing-switch-llm-based-ud/) · [**2021** 3 papers Carlos Gómez-Rodríguez's papers of 2021](https://md.research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/year/2021/) · [**2020** 3 papers Carlos Gómez-Rodríguez's papers of 2020](https://md.research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/year/2020/)

### 2010s

[**2019** 1 paper Carlos Gómez-Rodríguez's papers of 2019](https://md.research.elamur.ai/free/en/papers/vilares-2019-head-qa-healthcare-dataset-complex/) · [**2017** 1 paper Carlos Gómez-Rodríguez's papers of 2017](https://md.research.elamur.ai/free/en/papers/vilares-2017-non-projective-greedy-dependency-parser/) · [**2010** 1 paper Carlos Gómez-Rodríguez's papers of 2010](https://md.research.elamur.ai/free/en/papers/nivre-2010-evaluation-dependency-parsers-unbounded-dependencies/)

## Papers

The most cited first (OpenAlex and our library).

1. **[HEAD-QA: A Healthcare Dataset for Complex Reasoning](https://md.research.elamur.ai/free/en/papers/vilares-2019-head-qa-healthcare-dataset-complex/)** *(2019 · 104 citations)* HEAD-QA addresses a gap in question answering resources. Popular benchmarks such as SQuAD and bAbI can often be solved with surface-level cues, and existing reasoning-oriented datasets are mostly limited to grade-school science. To provide a harder, specialist-level test, Vilares and Gómez-Rodríguez collected…
2. **[Evaluation of Dependency Parsers on Unbounded Dependencies](https://md.research.elamur.ai/free/en/papers/nivre-2010-evaluation-dependency-parsers-unbounded-dependencies/)** *(2010 · 85 citations)* Unbounded dependencies, such as an object that is extracted from a relative clause, are a standard test of grammar-based parsers, but had not been applied to dependency parsers.
3. **[Distilling Neural Networks for Greener and Faster Dependency Parsing](https://md.research.elamur.ai/free/en/papers/anderson-2020-distilling-neural-networks-greener-faster/)** *(2020 · 32 citations)* The paper looks for a way to make dependency parsing computationally cheaper and less harmful to the environment with almost no loss in quality.
4. **[On the Frailty of Universal POS Tags for Neural UD Parsers](https://md.research.elamur.ai/free/en/papers/anderson-2020-frailty-universal-pos-tags-neural/)** *(2020 · 20 citations)* The paper asks whether universal POS (UPOS) tags still help modern neural dependency parsers that already use character-level representations.
5. **[A non-projective greedy dependency parser with bidirectional LSTMs](https://md.research.elamur.ai/free/en/papers/vilares-2017-non-projective-greedy-dependency-parser/)** *(2017 · 12 citations)* BIST-COVINGTON is a greedy parser that implements Covington's algorithm for unrestricted non-projective dependency parsing as a transition system, with O(n^2) complexity.
6. **[A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021](https://md.research.elamur.ai/free/en/papers/anderson-2021-modest-pareto-optimisation-analysis-dependency/)** *(2021 · 10 citations)* The authors compare modern dependency parsers on two criteria at once: parsing quality and resource cost. They take one representative from each of three approaches: a transition-based parser built on a pointer network (L2R), the graph-based Biaffine, and a parser that reduces parsing to sequence labeling (SeqLab).…
7. **[Parsing the Switch: LLM-Based UD Annotation for Complex Code-Switched and Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/kellert-2025-parsing-switch-llm-based-ud/)** *(2025 · 5 citations)* The paper tackles syntactic annotation of code-switched text, where monolingual parsers generalise poorly and annotated data hardly exists.
8. **[Inherent Dependency Displacement Bias of Transition-Based Algorithms](https://md.research.elamur.ai/free/en/papers/anderson-2020-inherent-dependency-displacement-bias-transition/)** *(2020 · 5 citations)* The paper defines an algorithm's inherent dependency displacement distribution: the distribution of signed head-dependent distances that the algorithm produces when it picks transitions at random, which needs no training data.
9. **[A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing](https://md.research.elamur.ai/free/en/papers/anderson-2021-falta-de-pan-buenas-son/)** *(2021 · 3 citations)* The authors examine whether automatically predicted UPOS tags should be given to a neural dependency parser as features when annotated data are scarce.
10. **[Splitting EUD Graphs into Trees: A Quick and Clatty Approach](https://md.research.elamur.ai/free/en/papers/anderson-2021-splitting-eud-graphs-into-trees/)** *(2021 · 2 citations)* The paper describes the FASTPARSE team's system for the IWPT 2021 shared task, which requires building Enhanced Universal Dependencies (EUD) graphs.
11. **[Sequence Labeling for Constituent Parsing: A Comparative Study and Encoding Innovations](https://md.research.elamur.ai/free/en/papers/roca-2026-sequence-labeling-constituent-parsing-comparative/)** *(2026)* Several schemes exist for turning constituent parsing into sequence labeling, where each word gets exactly one label that encodes part of the phrase-structure tree.

## Co-authors here

5 co-authors with a page, the most papers together first.

- [Mark Anderson](https://md.research.elamur.ai/free/en/authors/mark-anderson/) ×6
- [David Vilares](https://md.research.elamur.ai/free/en/authors/david-vilares/) ×3
- [Joakim Nivre](https://md.research.elamur.ai/free/en/authors/joakim-nivre/)
- [Laura Rimell](https://md.research.elamur.ai/free/en/authors/laura-rimell/)
- [Ryan McDonald](https://md.research.elamur.ai/free/en/authors/ryan-mcdonald/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [International Conference on Parsing Technologies and the IWPT Shared Task on Parsing into Enhanced Universal Dependencies](https://md.research.elamur.ai/free/en/venues/iwpt/) ×4: [International Conference on Parsing Technologies and the IWPT Shared Task on Parsing into Enhanced Universal Dependencies 2021](https://md.research.elamur.ai/free/en/venues/iwpt/2021/) ×3, [International Conference on Parsing Technologies and the IWPT Shared Task on Parsing into Enhanced Universal Dependencies 2020](https://md.research.elamur.ai/free/en/venues/iwpt/2020/)
- [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/) ×2: [CoNLL 2020](https://md.research.elamur.ai/free/en/venues/conll/2020/), [CoNLL 2017](https://md.research.elamur.ai/free/en/venues/conll/2017/)
- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2019](https://md.research.elamur.ai/free/en/venues/acl/2019/)
- [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/): [Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/cl/2026/)
- [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2010](https://md.research.elamur.ai/free/en/venues/coling/2010/)
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2025](https://md.research.elamur.ai/free/en/venues/findings/2025/)
- [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/): [LREC 2020](https://md.research.elamur.ai/free/en/venues/lrec/2020/)

## Cited by

Papers of our library cite their works 130 times (of the 141,840 papers whose bibliographies we read); [17 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/carlos-gomez-rodriguez/cited-by/).

Updated 24 October 2026
