Listar Lingua e Sociedade da Información (Language in the Information Society) (LYS) por autor "Muñoz-Ortiz, Alberto"

Mostrando ítems 1-5 de 5

    • Another Dead End for Morphological Tags? Perturbed Inputs and Parsing 

      Muñoz-Ortiz, Alberto; Vilares, David (Association for Computational Linguistics, 2023-07)
      [Absctract]: 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 tags and high quality written ...

    • Assessment of Pre-Trained Models Across Languages and Grammars 

      Muñoz-Ortiz, Alberto; Vilares, David; Gómez-Rodríguez, Carlos (Association for Computational Linguistics, 2023-11)
      [Absctract]: 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 dependency structures by ...

    • Cross-lingual Inflection as a Data Augmentation Method for Parsing 

      Muñoz-Ortiz, Alberto; Gómez-Rodríguez, Carlos; Vilares, David (Association for Computational Linguistics, 2022-05)
      [Absctract]: 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) treebanks to create ...

    • Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing 

      Muñoz-Ortiz, Alberto; Strzyz, Michalina; Vilares, David (INCOMA Ltd., 2021-09)
      [Absctract]: 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 the token arcs as bracket ...

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

      Muñoz-Ortiz, Alberto; Anderson, Mark; Vilares, David; Gómez-Rodríguez, Carlos (Association for Computational Linguistics, 2022-11)
      [Absctract]: 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 tags on graph- and ...