7 citations · 11 across the 11 of their papers we have counts for
12 papers
GRAMformer: Any-Order Modality Interactions via Volumetric Multimodal Cross-Attention
Giordano Cicchetti, Eleonora Grassucci, Danilo Comminiello
Transformer-based multimodal models rely on attention mechanisms to integrate information across heterogeneous modalities. Despite their success, existing multimodal attention form…
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…
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…
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…
A TRIANGLE Enables Multimodal Alignment Beyond Cosine Similarity
Giordano Cicchetti, Eleonora Grassucci, Danilo Comminiello
Multimodal learning plays a pivotal role in advancing artificial intelligence systems by incorporating information from multiple modalities to build a more comprehensive representa…
Training-Free Multimodal Guidance for Video to Audio Generation
Eleonora Grassucci, Giuliano Galadini, Giordano Cicchetti +3
Video-to-audio (V2A) generation aims to synthesize realistic and semantically aligned audio from silent videos, with potential applications in video editing, Foley sound design, an…
Semantic Compression via Multimodal Representation Learning
Eleonora Grassucci, Giordano Cicchetti, Aurelio Uncini +1
Multimodal representation learning produces high-dimensional embeddings that align diverse modalities in a shared latent space. While this enables strong generalization, it also in…
Gramian Multimodal Representation Learning and Alignment
Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo +1
Human perception integrates multiple modalities, such as vision, hearing, and language, into a unified understanding of the surrounding reality. While recent multimodal models have…
Lightweight Diffusion Models for Resource-Constrained Semantic Communication
Giovanni Pignata, Eleonora Grassucci, Giordano Cicchetti +1
Recently, generative semantic communication models have proliferated as they are revolutionizing semantic communication frameworks, improving their performance, and opening the way…
Language-Oriented Semantic Latent Representation for Image Transmission
Giordano Cicchetti, Eleonora Grassucci, Jihong Park +3
In the new paradigm of semantic communication (SC), the focus is on delivering meanings behind bits by extracting semantic information from raw data. Recent advances in data-to-tex…
Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling
Eleonora Grassucci, Jinho Choi, Jihong Park +3
In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the higher quality of transmitted information…
NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement
Giordano Cicchetti, Danilo Comminiello
Real-world documents may suffer various forms of degradation, often resulting in lower accuracy in optical character recognition (OCR) systems. Therefore, a crucial preprocessing s…