3 citations · 5 across the 29 of their papers we have counts for
31 papers
ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains
Artemis Llabrés, Marc Serra Ortega, Tomàs Ockier +6
In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to advance research in document un…
Rethinking Expert Training for Model Merging with Prompt Learning
Christos Georgakilas, Aniello Panariello, Samir El Karrat Moreno +3
Model merging aims to combine multiple domain-specialized experts trained from a shared foundation model into a single multi-task model. Existing approaches largely focus on improv…
SMI: Efficient Self-Supervised Learning via Mutual-Information-Inspired Dependency Optimization
Pritam Mishra, Coloma Ballester, Dimosthenis Karatzas
Self-supervised learning (SSL) has achieved remarkable representation learning performance, but many existing methods rely on large batch sizes, memory banks, momentum encoders, or…
Learning Quantifiable Visual Explanations Without Ground-Truth
Amritpal Singh, Andrey Barsky, Mohamed Ali Souibgui +2
Explainable AI (XAI) techniques are increasingly important for the validation and responsible use of modern deep learning models, but are difficult to evaluate due to the lack of g…
TRIMMER: A New Paradigm for Video Summarization through Self-Supervised Reinforcement Learning
Pritam Mishra, Coloma Ballester, Dimosthenis Karatzas
The rapid growth of video content across domains such as surveillance, education, and social media has made efficient content understanding increasingly critical. Video summarizati…
Reading in the Dark: Low-light Scene Text Recognition
Xuanshuo Fu, Lei Kang, Ernest Valveny +2
Accurate text recognition in low-light environments is essential for intelligent systems in applications ranging from autonomous vehicles to smart surveillance. However, challenges…
Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document Collections
Łukasz Borchmann, Jordy Van Landeghem, Michał Turski +12
Multimodal agents offer a promising path to automating complex document-intensive workflows. Yet, a critical question remains: do these agents demonstrate genuine strategic reasoni…
AVIR: Adaptive Visual In-Document Retrieval for Efficient Multi-Page Document Question Answering
Zongmin Li, Yachuan Li, Lei Kang +2
Multi-page Document Visual Question Answering (MP-DocVQA) remains challenging because long documents not only strain computational resources but also reduce the effectiveness of th…
Counterfeit Answers: Adversarial Forgery against OCR-Free Document Visual Question Answering
Marco Pintore, Maura Pintor, Dimosthenis Karatzas +1
Document Visual Question Answering (DocVQA) enables end-to-end reasoning grounded on information present in a document input. While recent models have shown impressive capabilities…
Spatially Grounded Explanations in Vision Language Models for Document Visual Question Answering
Maximiliano Hormazábal Lagos, Héctor Cerezo-Costas, Dimosthenis Karatzas
We introduce EaGERS, a fully training-free and model-agnostic pipeline that (1) generates natural language rationales via a vision language model, (2) grounds these rationales to s…
CoSMo: A Multimodal Transformer for Page Stream Segmentation in Comic Books
Marc Serra Ortega, Emanuele Vivoli, Artemis Llabrés +1
This paper introduces CoSMo, a novel multimodal Transformer for Page Stream Segmentation (PSS) in comic books, a critical task for automated content understanding, as it is a neces…
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…
TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness
Pritam Mishra, Coloma Ballester, Dimosthenis Karatzas
The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarization and video highlights as a vit…
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…
NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding
Aniket Pal, Sanket Biswas, Alloy Das +6
Understanding and reasoning over academic handwritten notes remains a challenge in document AI, particularly for mathematical equations, diagrams, and scientific notations. Existin…
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…
ComicsPAP: understanding comic strips by picking the correct panel
Emanuele Vivoli, Artemis Llabrés, Mohamed Ali Souibgui +3
Large multimodal models (LMMs) have made impressive strides in image captioning, VQA, and video comprehension, yet they still struggle with the intricate temporal and spatial cues…
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
Khanh Nguyen, Raouf Kerkouche, Mario Fritz +1
Document Visual Question Answering (DocVQA) has introduced a new paradigm for end-to-end document understanding, and quickly became one of the standard benchmarks for multimodal LL…
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA
Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito +24
The Privacy Preserving Federated Learning Document VQA (PFL-DocVQA) competition challenged the community to develop provably private and communication-efficient solutions in a fede…
ComiCap: A VLMs pipeline for dense captioning of Comic Panels
Emanuele Vivoli, Niccolò Biondi, Marco Bertini +1
The comic domain is rapidly advancing with the development of single- and multi-page analysis and synthesis models. Recent benchmarks and datasets have been introduced to support a…
One missing piece in Vision and Language: A Survey on Comics Understanding
Emanuele Vivoli, Mohamed Ali Souibgui, Andrey Barsky +3
Vision-language models have recently evolved into versatile systems capable of high performance across a range of tasks, such as document understanding, visual question answering,…
GRIF-DM: Generation of Rich Impression Fonts using Diffusion Models
Lei Kang, Fei Yang, Kai Wang +5
Fonts are integral to creative endeavors, design processes, and artistic productions. The appropriate selection of a font can significantly enhance artwork and endow advertisements…
Image-text matching for large-scale book collections
Artemis Llabrés, Arka Ujjal Dey, Dimosthenis Karatzas +1
We address the problem of detecting and mapping all books in a collection of images to entries in a given book catalogue. Instead of performing independent retrieval for each book…