16 citations · 16 across the 3 of their papers we have counts for
5 papers
RFMI: Estimating Mutual Information on Rectified Flow for Text-to-Image Alignment
Chao Wang, Giulio Franzese, Alessandro Finamore +1
Rectified Flow (RF) models trained with a Flow matching framework have achieved state-of-the-art performance on Text-to-Image (T2I) conditional generation. Yet, multiple benchmarks…
Information Theoretic Text-to-Image Alignment
Chao Wang, Giulio Franzese, Alessandro Finamore +2
Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a labori…
Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
Data Augmentation (DA) -- enriching training data by adding synthetic samples -- is a technique widely adopted in Computer Vision (CV) and Natural Language Processing (NLP) tasks t…
Toward Generative Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
Data Augmentation (DA)-augmenting training data with synthetic samples-is wildly adopted in Computer Vision (CV) to improve models performance. Conversely, DA has not been yet popu…
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation
Alessandro Finamore, Chao Wang, Jonatan Krolikowski +3
Over the last years we witnessed a renewed interest toward Traffic Classification (TC) captivated by the rise of Deep Learning (DL). Yet, the vast majority of TC literature lacks c…