most citedDetecting and explaining postpartum depression in real-time with generative artificial intelligence

10 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI20253 cited

Explainable e-sports win prediction through Machine Learning classification in streaming

Silvia García-Méndez, Francisco de Arriba-Pérez

The increasing number of spectators and players in e-sports, along with the development of optimized communication solutions and cloud computing technology, has motivated the const…

cs.CL20252 cited

Unraveling Emotions with Pre-Trained Models

Alejandro Pajón-Sanmartín, Francisco De Arriba-Pérez, Silvia García-Méndez +3

Transformer models have significantly advanced the field of emotion recognition. However, there are still open challenges when exploring open-ended queries for Large Language Model…

cs.CL202510 cited

Detecting and explaining postpartum depression in real-time with generative artificial intelligence

Silvia García-Méndez, Francisco de Arriba-Pérez

Among the many challenges mothers undergo after childbirth, postpartum depression (PPD) is a severe condition that significantly impacts their mental and physical well-being. Conse…

cs.CL2025

Optimal word order for non-causal text generation with Large Language Models: the Spanish case

Andrea Busto-Castiñeira, Silvia García-Méndez, Francisco de Arriba-Pérez +1

Natural Language Generation (NLG) popularity has increased owing to the progress in Large Language Models (LLMs), with zero-shot inference capabilities. However, most neural system…

cs.IR2025

Identification and explanation of disinformation in wiki data streams

Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2

Social media platforms, increasingly used as news sources for varied data analytics, have transformed how information is generated and disseminated. However, the unverified nature…