4 citations · 6 across the 4 of their papers we have counts for
4 papers
Boosting Deep Reinforcement Learning with Semantic Knowledge for Robotic Manipulators
Lucía Güitta-López, Vincenzo Suriani, Jaime Boal +2
Deep Reinforcement Learning (DRL) is a powerful framework for solving complex sequential decision-making problems, particularly in robotic control. However, its practical deploymen…
Sim-to-Real Transfer via a Style-Identified Cycle Consistent Generative Adversarial Network: Zero-Shot Deployment on Robotic Manipulators through Visual Domain Adaptation
Lucía Güitta-López, Lionel Güitta-López, Jaime Boal +1
The sample efficiency challenge in Deep Reinforcement Learning (DRL) compromises its industrial adoption due to the high cost and time demands of real-world training. Virtual envir…
VERSE: Visual Embedding Reduction and Space Exploration. Clustering-Guided Insights for Training Data Enhancement in Visually-Rich Document Understanding
Ignacio de Rodrigo, Alvaro J. Lopez-Lopez, Jaime Boal
This work introduces VERSE, a methodology for analyzing and improving Vision-Language Models applied to Visually-rich Document Understanding by exploring their visual embedding spa…
The MERIT Dataset: Modelling and Efficiently Rendering Interpretable Transcripts
I. de Rodrigo, A. Sanchez-Cuadrado, J. Boal +1
This paper introduces the MERIT Dataset, a multimodal (text + image + layout) fully labeled dataset within the context of school reports. Comprising over 400 labels and 33k samples…