Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT).
The community proposed specific network architectures and learning-based methods to …

In this work, we define a diffusion-based generative model capable of both music synthesis
and source separation by learning the score of the joint probability density of sources …

Abstract In recent years Large Language Models have improved the state of the art on
several natural language processing tasks. However, their availability is frequently restricted …

We present COCOLA (Coherence-Oriented Contrastive Learning for Audio), a contrastive
learning method for musical audio representations that captures the harmonic and rhythmic …

Current generative models are able to generate high-quality artefacts but have been shown
to struggle with compositional reasoning, which can be defined as the ability to generate …

enpresa Management Letters / Cuadernos de Gestión Page 1 This article is distributed under the
terms of the Creative Commons Atribution 4.0 Internacional License institutua enpresa Instituto …

In this work, we demonstrate the integration of a score-matching diffusion model into a
deterministic architecture for time-domain musical source extraction, resulting in enhanced …

The marine ecosystem faces alarming changes, including biodiversity loss and the migration
of tropical species to temperate regions. Monitoring underwater environments and their …

I developed a neural audio codec model based on the residual quantized variational
autoencoder architecture. I train the model on the Slakh2100 dataset, a standard dataset for …

Generative models have experienced significant advancements in recent years, driven by
the introduction of architectures such as Stable Diffusion, GPT-3, ChatGPT, and many …