Publications and research
Research
My research focuses on structured, multilingual, and robust NLP. I work on efficient modeling approaches, cross-lingual transfer, and rigorous evaluation of language models. I have first-authored 8 papers at top NLP venues.
2025
- Alberto Muñoz-Ortiz, David Vilares, Caio Corro, and Carlos Gómez-Rodríguez. Nested Named Entity Recognition as Single-Pass Sequence labeling. In Findings of EMNLP 2025, Suzhou, China.
- Alberto Muñoz-Ortiz, Verena Blaschke, and Barbara Plank. Evaluating Pixel Language Models on Non-Standardized Languages. In COLING 2025, Abu Dhabi, UAE.
- Inés Veiga Menéndez, Alberto Muñoz-Ortiz, and David Vilares. On the Impact of Syntactic Infusion for Gender Categorization Across Contextual Dimensions. In Revista de Procesamiento de Lenguaje Natural, 2025.
2024
- Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, and David Vilares. Contrasting Linguistic Patterns in Human and LLM-Generated News Text. In Artificial Intelligence Review, 2024.
- Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez and David Vilares. Demographic Background Prompting Does Not Affect Linguistic Features on LLM-Generated News Texts. In XoveTIC 2024.
2023
- Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, and David Vilares. Assessment of Pre-Trained Models Across Languages and Grammars. In IJCNLP-AACL 2023, Bali, Indonesia.
- Alberto Muñoz-Ortiz and David Vilares. LyS A Coruña at GUA-SPA@IberLEF2023: Multi-Task Learning with Large Language Model Encoders for Guarani-Spanish Code Switching Analysis. In IberLEF 2023, Jaén, Spain.
- Alberto Muñoz-Ortiz and David Vilares. Another Dead End for Morphological Tags? Perturbed Inputs and Parsing. In Findings of ACL 2023, Toronto, Canada.
2022
- Alberto Muñoz-Ortiz, Mark Anderson, David Vilares, and Carlos Gómez-Rodríguez. Parsing Linearizations Appreciate PoS Tags – but Some Are Fussy about Errors. In IJCNLP-AACL 2022, Online.
- Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, and David Vilares. Cross-lingual Inflection as a Data Augmentation Method. In the 3rd Workshop on Insights from Negative Results in NLP, Dublin, Ireland.
2021
- Alberto Muñoz-Ortiz, Michalina Strzyz, and David Vilares. Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing. In RANLP 2021, Online.