Papers by L. Alfonso Ureña
Nuanced Toxicity Detection in Spanish: A New Corpus and Benchmark Study (2026.findings-eacl)
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Alba María Mármol-Romero, Robiert Sepúlveda-Torres, Estela Saquete, María-Teresa Martín-Valdivia, L. Alfonso Ureña
| Challenge: | Existing corpora for Spanish are under-resourced for toxic content detection . sarcasm, indirect aggression, irony, and other toxicity are not detected in English . |
| Approach: | They propose to extend the NECOS-TOX corpus to include 4,011 Spanish comments . each comment is annotated across three levels of toxicity, with substantial inter-annotator agreement . |
| Outcome: | The proposed model performs on par with larger models and is released publicly . the proposed model is based on a human-in-the-loop active learning strategy . |
The Problem of Ambiguity in Table Question Answering (2026.findings-eacl)
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| Challenge: | Existing approaches to question answering on tabular data have limited capabilities due to ambiguousness inherent to tabular datasets. |
| Approach: | They propose to use large language models to answer questions on tabular data by analyzing tabular tables and detecting ambiguity. |
| Outcome: | The proposed model can detect ambiguity in tabular data and provide an initial ground for a deeper discussion on how to approach it in the age of LLMs. |