67 citations · 80 across the 18 of their papers we have counts for
4 papers · 1 filter
Multimodal Large Language Models for Low-Resource Languages: A Case Study for Basque
Lukas Arana, Julen Etxaniz, Ander Salaberria +1
Current Multimodal Large Language Models exhibit very strong performance for several demanding tasks. While commercial MLLMs deliver acceptable performance in low-resource language…
Multimodal LLMs Do Not Compose Skills Optimally Across Modalities
Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune
Skill composition is the ability to combine previously learned skills to solve new tasks. As neural networks acquire increasingly complex skills during their pretraining, it is not…
Adding simple structure at inference improves Vision-Language Compositionality
Imanol Miranda, Ander Salaberria, Eneko Agirre +1
Dual encoder Vision-Language Models (VLM) such as CLIP are widely used for image-text retrieval tasks. However, those models struggle with compositionality, showing a bag-of-words-…
Vision-Language Models Struggle to Align Entities across Modalities
Iñigo Alonso, Gorka Azkune, Ander Salaberria +2
Cross-modal entity linking refers to the ability to align entities and their attributes across different modalities. While cross-modal entity linking is a fundamental skill needed…