8 citations · 10 across the 7 of their papers we have counts for
8 papers
Domyn-Small: A European 10B Reasoning Language Model
Simone Angarano, Francesco Bertolotti, Federico D'Ambrosio +7
We introduce Domyn-Small, a 10-billion-parameter open-weight reasoning language model released under the MIT license. Domyn-Small is the product of an initial pre-training phase on…
Graph-based Polyphonic Multitrack Music Generation
Emanuele Cosenza, Andrea Valenti, Davide Bacciu
Graphs can be leveraged to model polyphonic multitrack symbolic music, where notes, chords and entire sections may be linked at different levels of the musical hierarchy by tonal a…
ChemAlgebra: Algebraic Reasoning on Chemical Reactions
Andrea Valenti, Davide Bacciu, Antonio Vergari
While showing impressive performance on various kinds of learning tasks, it is yet unclear whether deep learning models have the ability to robustly tackle reasoning tasks. than by…
Modular Representations for Weak Disentanglement
Andrea Valenti, Davide Bacciu
The recently introduced weakly disentangled representations proposed to relax some constraints of the previous definitions of disentanglement, in exchange for more flexibility. How…
Leveraging Relational Information for Learning Weakly Disentangled Representations
Andrea Valenti, Davide Bacciu
Disentanglement is a difficult property to enforce in neural representations. This might be due, in part, to a formalization of the disentanglement problem that focuses too heavily…
Calliope -- A Polyphonic Music Transformer
Andrea Valenti, Stefano Berti, Davide Bacciu
The polyphonic nature of music makes the application of deep learning to music modelling a challenging task. On the other hand, the Transformer architecture seems to be a good fit…
ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs
Andrea Valenti, Michele Barsotti, Raffaello Brondi +2
Typical EEG-based BCI applications require the computation of complex functions over the noisy EEG channels to be carried out in an efficient way. Deep learning algorithms are capa…
Learning Style-Aware Symbolic Music Representations by Adversarial Autoencoders
Andrea Valenti, Antonio Carta, Davide Bacciu
We address the challenging open problem of learning an effective latent space for symbolic music data in generative music modeling. We focus on leveraging adversarial regularizatio…