13 citations · 15 across the 10 of their papers we have counts for
10 papers
CURE: Curriculum-guided Multi-task Training for Reliable Anatomy Grounded Report Generation
Pablo Messina, Andrés Villa, Juan León Alcázar +5
Medical vision-language models can automate the generation of radiology reports but struggle with accurate visual grounding and factual consistency. Existing models often misalign…
MoDA: Modulation Adapter for Fine-Grained Visual Grounding in Instructional MLLMs
Wayner Barrios, Andrés Villa, Juan León Alcázar +2
Multimodal Large Language Models (MLLMs) have achieved remarkable success in instruction-following tasks by integrating pretrained visual encoders with large language models (LLMs)…
Towards Faster and More Compact Foundation Models for Molecular Property Prediction
Yasir Ghunaim, Andrés Villa, Gergo Ignacz +3
Advancements in machine learning for molecular property prediction have improved accuracy but at the expense of higher computational cost and longer training times. Recently, the J…
EAGLE: Enhanced Visual Grounding Minimizes Hallucinations in Instructional Multimodal Models
Andrés Villa, Juan León Alcázar, Motasem Alfarra +3
Large language models and vision transformers have demonstrated impressive zero-shot capabilities, enabling significant transferability in downstream tasks. The fusion of these mod…
Behind the Magic, MERLIM: Multi-modal Evaluation Benchmark for Large Image-Language Models
Andrés Villa, Juan Carlos León Alcázar, Alvaro Soto +1
Large Vision and Language Models have enabled significant advances in fully supervised and zero-shot visual tasks. These large architectures serve as the baseline to what is curren…
PIVOT: Prompting for Video Continual Learning
Andrés Villa, Juan León Alcázar, Motasem Alfarra +5
Modern machine learning pipelines are limited due to data availability, storage quotas, privacy regulations, and expensive annotation processes. These constraints make it difficult…
vCLIMB: A Novel Video Class Incremental Learning Benchmark
Andrés Villa, Kumail Alhamoud, Juan León Alcázar +3
Continual learning (CL) is under-explored in the video domain. The few existing works contain splits with imbalanced class distributions over the tasks, or study the problem in uns…
Augmenting BERT-style Models with Predictive Coding to Improve Discourse-level Representations
Vladimir Araujo, Andrés Villa, Marcelo Mendoza +2
Current language models are usually trained using a self-supervised scheme, where the main focus is learning representations at the word or sentence level. However, there has been…
TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video Classification
Andrés Villa, Juan-Manuel Perez-Rua, Victor Escorcia +3
Recently, few-shot video classification has received an increasing interest. Current approaches mostly focus on effectively exploiting the temporal dimension in videos to improve l…
Interpretable Contextual Team-aware Item Recommendation: Application in Multiplayer Online Battle Arena Games
Andrés Villa, Vladimir Araujo, Francisca Cattan +1
The video game industry has adopted recommendation systems to boost users interest with a focus on game sales. Other exciting applications within video games are those that help th…