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Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions
Large Language Models (LLMs) represent a significant advancement in artificial intelligence, finding applications across various …
Michele Miranda
,
Elena Sofia Ruzzetti
,
Andrea Santilli
,
Fabio Massimo Zanzotto
,
Sebastien Bratieres
,
Emanuele Rodolà
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arXiv
Graph Kernel Neural Networks
The convolution operator at the core of many modern neural architectures can effectively be seen as performing a dot product between an …
Luca Cosmo
,
Giorgia Minello
,
Alessandro Bicciato
,
Michael Bronstein
,
Emanuele Rodolà
,
Luca Rossi
,
Andrea Torsello
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arXiv
Latent spectral regularization for continual learning
While biological intelligence grows organically as new knowledge is gathered throughout life, Artificial Neural Networks forget …
Emanuele Frascaroli
,
Riccardo Benaglia
,
Matteo Boschini
,
Luca Moschella
,
Cosimo Fiorini
,
Emanuele Rodolà
,
Simone Calderara
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arXiv
GitHub
A Physically-inspired Approach to the Simulation of Plant Wilting
Plants are among the most complex objects to be modeled in computer graphics. While a large body of work is concerned with structural …
Filippo Maggioli
,
Jonathan Klein
,
Torsten Hadrich
,
Emanuele Rodolà
,
Wojtek Palubicki
,
Soren Pirk
,
Dominik Michels
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ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training
CLIP proved that aligning visual and language spaces is key to solving many vision tasks without explicit training, but required to …
Antonio Norelli
,
Marco Fumero
,
Valentino Maiorca
,
Luca Moschella
,
Emanuele Rodolà
,
Francesco Locatello
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arXiv
Poster
Thread
GitHub
NeurIPS 2023
Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation
The marine ecosystem is changing at an alarming rate, exhibiting biodiversity loss and the migration of tropical species to temperate …
Michele Mancusi
,
Nicola Zonca
,
Emanuele Rodolà
,
Silvia Zuffi
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Bootstrapping Parallel Anchors for Relative Representations
The use of relative representations for latent embeddings has shown potential in enabling latent space communication and zero-shot …
Irene Cannistraci
,
Luca Moschella
,
Valentino Maiorca
,
Marco Fumero
,
Antonio Norelli
,
Emanuele Rodolà
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Certification of Gaussian Boson Sampling via graphs feature vectors and kernels
Gaussian Boson Sampling (GBS) is a non-universal model for quantum computing inspired by the original formulation of the Boson Sampling …
Taira Giordani
,
Valerio Mannucci
,
Nicolò Spagnolo
,
Marco Fumero
,
Arianna Rampini
,
Emanuele Rodolà
,
Fabio Sciarrino
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Few-Shot Object Detection: A Survey
Deep learning approaches have recently raised the bar in many fields, from Natural Language Processing to Computer Vision, by …
Simone Antonelli
,
Danilo Avola
,
Luigi Cinque
,
Donato Crisostomi
,
Gian Luca Foresti
,
Fabio Galasso
,
Marco Raoul Marini
,
Alessio Mecca
,
Daniele Pannone
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Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification
Computer-aided diagnosis (CAD) is becoming a prominent approach to assist clinicians spanning across multiple fields. These automated …
Danilo Avola
,
Luigi Cinque
,
Alessio Fagioli
,
Sebastiano Filetti
,
Giorgio Grani
,
Emanuele Rodolà
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