71 citations · 71 across the 8 of their papers we have counts for
8 papers
Nested Named Entity Recognition as Single-Pass Sequence Labeling
Alberto Muñoz-Ortiz, David Vilares, Caio Corro +1
We cast nested named entity recognition (NNER) as a sequence labeling task by leveraging prior work that linearizes constituency structures, effectively reducing the complexity of…
Evaluating Pixel Language Models on Non-Standardized Languages
Alberto Muñoz-Ortiz, Verena Blaschke, Barbara Plank
We explore the potential of pixel-based models for transfer learning from standard languages to dialects. These models convert text into images that are divided into patches, enabl…
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…
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…
Another Dead End for Morphological Tags? Perturbed Inputs and Parsing
Alberto Muñoz-Ortiz, David Vilares
The usefulness of part-of-speech tags for parsing has been heavily questioned due to the success of word-contextualized parsers. Yet, most studies are limited to coarse-grained tag…
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…
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…
Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing
Alberto Muñoz-Ortiz, Michalina Strzyz, David Vilares
Different linearizations have been proposed to cast dependency parsing as sequence labeling and solve the task as: (i) a head selection problem, (ii) finding a representation of th…