477 citations · 819 across the 59 of their papers we have counts for
61 papers
Closing the gap in multimodal medical representation alignment
Eleonora Grassucci, Giordano Cicchetti, Danilo Comminiello
In multimodal learning, CLIP has emerged as the de-facto approach for mapping different modalities into a shared latent space by bringing semantically similar representations close…
The IJCNN 2025 Review Process
Michele Scarpiniti, Danilo Comminiello
The International Joint Conference on Neural Networks (IJCNN) is the premier international conference in the area of neural networks theory, analysis, and applications. The 2025 ed…
Closing the Modality Gap Aligns Group-Wise Semantics
Eleonora Grassucci, Giordano Cicchetti, Emanuele Frasca +2
In multimodal learning, CLIP has been recognized as the \textit{de facto} method for learning a shared latent space across multiple modalities, placing similar representations clos…
Generative Models for Helmholtz Equation Solutions: A Dataset of Acoustic Materials
Riccardo Fosco Gramaccioni, Christian Marinoni, Fabrizio Frezza +2
Accurate simulation of wave propagation in complex acoustic materials is crucial for applications in sound design, noise control, and material engineering. Traditional numerical so…
Controllable Audio-Visual Viewpoint Generation from 360° Spatial Information
Christian Marinoni, Riccardo Fosco Gramaccioni, Eleonora Grassucci +1
The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to gen…
FoleyGRAM: Video-to-Audio Generation with GRAM-Aligned Multimodal Encoders
Riccardo Fosco Gramaccioni, Christian Marinoni, Eleonora Grassucci +3
In this work, we present FoleyGRAM, a novel approach to video-to-audio generation that emphasizes semantic conditioning through the use of aligned multimodal encoders. Building on…