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20222026
most citedRetrieval-Augmented Transformer for Image Captioning

9 citations · 14 across the 19 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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).…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning

Federico Cocchi, Nicholas Moratelli, Davide Caffagni +4

Recent progress in Multimodal Large Language Models (MLLMs) has highlighted the critical roles of both the visual backbone and the underlying language model. While prior work has p…

cs.CV2025

Image Captioning Evaluation in the Age of Multimodal LLMs: Challenges and Future Perspectives

Sara Sarto, Marcella Cornia, Rita Cucchiara

The evaluation of machine-generated image captions is a complex and evolving challenge. With the advent of Multimodal Large Language Models (MLLMs), image captioning has become a c…