478 citations · 905 across the 72 of their papers we have counts for
14 papers · 1 filter
Seeing Beyond Words: Self-Supervised Visual Learning for Multimodal Large Language Models
Davide Caffagni, Sara Sarto, Marcella Cornia +5
Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in connecting vision and language, yet their proficiency in fundamental visual reasoning…
ReAG: Reasoning-Augmented Generation for Knowledge-based Visual Question Answering
Alberto Compagnoni, Marco Morini, Sara Sarto +5
Multimodal Large Language Models (MLLMs) have shown impressive capabilities in jointly understanding text, images, and videos, often evaluated via Visual Question Answering (VQA).…
Recurrence Meets Transformers for Universal Multimodal Retrieval
Davide Caffagni, Sara Sarto, Marcella Cornia +2
With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have emerged. Existing methods predominantl…
Mitigating Hallucinations in Multimodal LLMs via Object-aware Preference Optimization
Alberto Compagnoni, Davide Caffagni, Nicholas Moratelli +3
Multimodal Large Language Models (MLLMs) emerge as a unified interface to address a multitude of tasks, ranging from NLP to computer vision. Despite showcasing state-of-the-art res…
Modeling Human Gaze Behavior with Diffusion Models for Unified Scanpath Prediction
Giuseppe Cartella, Vittorio Cuculo, Alessandro D'Amelio +3
Predicting human gaze scanpaths is crucial for understanding visual attention, with applications in human-computer interaction, autonomous systems, and cognitive robotics. While de…
RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image Detectors
Hicham Eddoubi, Jonas Ricker, Federico Cocchi +7
AI-generated images have reached a quality level at which humans are incapable of reliably distinguishing them from real images. To counteract the inherent risk of fraud and disinf…