37 citations · 115 across the 25 of their papers we have counts for
5 papers · 1 filter
Enhancing Document VQA Models via Retrieval-Augmented Generation
Eric López, Artemis Llabrés, Ernest Valveny
Document Visual Question Answering (Document VQA) must cope with documents that span dozens of pages, yet leading systems still concatenate every page or rely on very large vision-…
LLM-Driven Medical Document Analysis: Enhancing Trustworthy Pathology and Differential Diagnosis
Lei Kang, Xuanshuo Fu, Oriol Ramos Terrades +3
Medical document analysis plays a crucial role in extracting essential clinical insights from unstructured healthcare records, supporting critical tasks such as differential diagno…
DocVXQA: Context-Aware Visual Explanations for Document Question Answering
Mohamed Ali Souibgui, Changkyu Choi, Andrey Barsky +3
We propose DocVXQA, a novel framework for visually self-explainable document question answering. The framework is designed not only to produce accurate answers to questions but als…
xLSTM-ECG: Multi-label ECG Classification via Feature Fusion with xLSTM
Lei Kang, Xuanshuo Fu, Javier Vazquez-Corral +2
Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, highlighting the critical need for efficient and accurate diagnostic tools. Electrocardiograms (ECGs…
Preserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognition
Lei Kang, Xuanshuo Fu, Lluis Gomez +3
Handwritten Text Recognition (HTR) is crucial for document digitization, but handwritten data can contain user-identifiable features, like unique writing styles, posing privacy ris…