8 papers · 1 filter
Mind the Heads: Topological Representation Alignment for Multimodal LLMs
Davide Caffagni, Alberto Compagnoni, Federico Melis +5
Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal representations toward those of an…
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).…
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…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…
Recurrence-Enhanced Vision-and-Language Transformers for Robust Multimodal Document Retrieval
Davide Caffagni, Sara Sarto, Marcella Cornia +2
Cross-modal retrieval is gaining increasing efficacy and interest from the research community, thanks to large-scale training, novel architectural and learning designs, and its app…