most citedAn overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainability

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2025★ 2 cited

An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainability

David Herrera-Poyatos, Carlos Peláez-González, Cristina Zuheros +4

Large Language Models (LLMs) have significantly advanced sentiment analysis, yet their inherent uncertainty and variability pose critical challenges to achieving reliable and consi…

cs.CV2024★ 1 cited

Deep Learning methodology for the identification of wood species using high-resolution macroscopic images

David Herrera-Poyatos, Andrés Herrera-Poyatos, Rosana Montes +5

Significant advancements in the field of wood species identification are needed worldwide to support sustainable timber trade. In this work we contribute to automate the identifica…