activity
20122023
most citedContrasting Linguistic Patterns in Human and LLM-Generated News Text

71 citations · 410 across the 49 of their papers we have counts for

collaborators
Showing cs.CLShow all

70 papers · 1 filter

cs.CL2023

On the Challenges of Fully Incremental Neural Dependency Parsing

Ana Ezquerro, Carlos Gómez-Rodríguez, David Vilares

Since the popularization of BiLSTMs and Transformer-based bidirectional encoders, state-of-the-art syntactic parsers have lacked incrementality, requiring access to the whole sente…

cs.CL2023

Assessment of Pre-Trained Models Across Languages and Grammars

Alberto Muñoz-Ortiz, David Vilares, Carlos Gómez-Rodríguez

We present an approach for assessing how multilingual large language models (LLMs) learn syntax in terms of multi-formalism syntactic structures. We aim to recover constituent and…

cs.CL2023★ 2 cited

Experimenting with UD Adaptation of an Unsupervised Rule-based Approach for Sentiment Analysis of Mexican Tourist Texts

Olga Kellert, Mahmud Uz Zaman, Nicholas Hill Matlis +1

This paper summarizes the results of experimenting with Universal Dependencies (UD) adaptation of an Unsupervised, Compositional and Recursive (UCR) rule-based approach for Sentime…

cs.CL2023

Spanish Resource Grammar version 2023

Olga Zamaraeva, Lorena S. Allegue, Carlos Gómez-Rodríguez

We present the latest version of the Spanish Resource Grammar (SRG), a grammar of Spanish implemented in the HPSG formalism. Such grammars encode a complex set of hypotheses about…

cs.CL2023

Revisiting Supertagging for Faster HPSG Pasing

Olga Zamaraeva, Carlos Gómez-Rodríguez

We present new supertaggers trained on English grammar-based treebanks and test the effects of the best tagger on parsing speed and accuracy. The treebanks are produced automatical…

cs.CL2023★ 71 cited

Contrasting Linguistic Patterns in Human and LLM-Generated News Text

Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, David Vilares

We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different…

cs.CL2022

Parsing linearizations appreciate PoS tags - but some are fussy about errors

Alberto Muñoz-Ortiz, Mark Anderson, David Vilares +1

PoS tags, once taken for granted as a useful resource for syntactic parsing, have become more situational with the popularization of deep learning. Recent work on the impact of PoS…

cs.CL2022

The Impact of Edge Displacement Vaserstein Distance on UD Parsing Performance

Mark Anderson, Carlos Gómez-Rodríguez

We contribute to the discussion on parsing performance in NLP by introducing a measurement that evaluates the differences between the distributions of edge displacement (the direct…

cs.CL2022★ 1 cited

The Fragility of Multi-Treebank Parsing Evaluation

Iago Alonso-Alonso, David Vilares, Carlos Gómez-Rodríguez

Treebank selection for parsing evaluation and the spurious effects that might arise from a biased choice have not been explored in detail. This paper studies how evaluating on a si…

cs.CL2022

Cross-lingual Inflection as a Data Augmentation Method for Parsing

Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, David Vilares

We propose a morphology-based method for low-resource (LR) dependency parsing. We train a morphological inflector for target LR languages, and apply it to related rich-resource (RR…

cs.CL2022★ 7 cited

A machine transliteration tool between Uzbek alphabets

Ulugbek Salaev, Elmurod Kuriyozov, Carlos Gómez-Rodríguez

Machine transliteration, as defined in this paper, is a process of automatically transforming written script of words from a source alphabet into words of another target alphabet w…

cs.CL2022★ 4 cited

SimRelUz: Similarity and Relatedness scores as a Semantic Evaluation dataset for Uzbek language

Ulugbek Salaev, Elmurod Kuriyozov, Carlos Gómez-Rodríguez

Semantic relatedness between words is one of the core concepts in natural language processing, thus making semantic evaluation an important task. In this paper, we present a semant…

cs.CL2022

LyS_ACoruña at SemEval-2022 Task 10: Repurposing Off-the-Shelf Tools for Sentiment Analysis as Semantic Dependency Parsing

Iago Alonso-Alonso, David Vilares, Carlos Gómez-Rodríguez

This paper addressed the problem of structured sentiment analysis using a bi-affine semantic dependency parser, large pre-trained language models, and publicly available translatio…

cs.CL2021

Discontinuous Grammar as a Foreign Language

Daniel Fernández-González, Carlos Gómez-Rodríguez

In order to achieve deep natural language understanding, syntactic constituent parsing is a vital step, highly demanded by many artificial intelligence systems to process both text…

cs.CL2021★ 1 cited

Dependency distance minimization predicts compression

Ramon Ferrer-i-Cancho, Carlos Gómez-Rodríguez

Dependency distance minimization (DDm) is a well-established principle of word order. It has been predicted theoretically that DDm implies compression, namely the minimization of w…

cs.CL2021

Splitting EUD graphs into trees: A quick and clatty approach

Mark Anderson, Carlos Gómez-Rodríguez

We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2021. We engaged in the task last year by focusing on efficiency. This year we have focused…

cs.CL2021

A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021

Mark Anderson, Carlos Gómez Rodríguez

We evaluate three leading dependency parser systems from different paradigms on a small yet diverse subset of languages in terms of their accuracy-efficiency Pareto front. As we ar…

cs.CL2021

A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing

Mark Anderson, Mathieu Dehouck, Carlos Gómez Rodríguez

We evaluate the efficacy of predicted UPOS tags as input features for dependency parsers in lower resource settings to evaluate how treebank size affects the impact tagging accurac…

cs.CL2021

Dependency Parsing with Bottom-up Hierarchical Pointer Networks

Daniel Fernández-González, Carlos Gómez-Rodríguez

Dependency parsing is a crucial step towards deep language understanding and, therefore, widely demanded by numerous Natural Language Processing applications. In particular, left-t…

cs.CL2021★ 3 cited

What Taggers Fail to Learn, Parsers Need the Most

Mark Anderson, Carlos Gómez-Rodríguez

We present an error analysis of neural UPOS taggers to evaluate why using gold standard tags has such a large positive contribution to parsing performance while using predicted UPO…

cs.CL2021

Reducing Discontinuous to Continuous Parsing with Pointer Network Reordering

Daniel Fernández-González, Carlos Gómez-Rodríguez

Discontinuous constituent parsers have always lagged behind continuous approaches in terms of accuracy and speed, as the presence of constituents with discontinuous yield introduce…

cs.CL2021

Bertinho: Galician BERT Representations

David Vilares, Marcos Garcia, Carlos Gómez-Rodríguez

This paper presents a monolingual BERT model for Galician. We follow the recent trend that shows that it is feasible to build robust monolingual BERT models even for relatively low…

cs.CL2020

Bracketing Encodings for 2-Planar Dependency Parsing

Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez

We present a bracketing-based encoding that can be used to represent any 2-planar dependency tree over a sentence of length n as a sequence of n labels, hence providing almost tota…

cs.CL2020

A Unifying Theory of Transition-based and Sequence Labeling Parsing

Carlos Gómez-Rodríguez, Michalina Strzyz, David Vilares

We define a mapping from transition-based parsing algorithms that read sentences from left to right to sequence labeling encodings of syntactic trees. This not only establishes a t…