7 papers
Estimating Uncertainty from Reasoning: A Large-Scale Study of Multi- and Crosslingual MCQA Performance in LLMs
Andrea Bacciu, Andrea Alfarano, Saab Mansour +2
Uncertainty estimation (UE) enables LLM-powered systems to recognize when to abstain, yet existing research has predominantly focused on English. We present the first large-scale e…
R3ST: A Synthetic 3D Dataset With Realistic Trajectories
Simone Teglia, Claudia Melis Tonti, Francesco Pro +4
Datasets are essential to train and evaluate computer vision models used for traffic analysis and to enhance road safety. Existing real datasets fit real-world scenarios, capturing…
VQArt-Bench: A semantically rich VQA Benchmark for Art and Cultural Heritage
A. Alfarano, L. Venturoli, D. Negueruela del Castillo
Multimodal Large Language Models (MLLMs) have demonstrated significant capabilities in joint visual and linguistic tasks. However, existing Visual Question Answering (VQA) benchmar…
NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results
Lei Sun, Andrea Alfarano, Peiqi Duan +85
This paper presents an overview of NTIRE 2025 the First Challenge on Event-Based Image Deblurring, detailing the proposed methodologies and corresponding results. The primary goal…
Training-Free Style and Content Transfer by Leveraging U-Net Skip Connections in Stable Diffusion
Ludovica Schaerf, Andrea Alfarano, Fabrizio Silvestri +1
Recent advances in diffusion models for image generation have led to detailed examinations of several components within the U-Net architecture for image editing. While previous stu…
STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing
Andrea Alfarano, Alberto Alfarano, Linda Friso +3
Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past f…