The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with
large language models (LLMs) and computer vision (CV) systems driving advancements in …

In the face of a new era of generative models, the detection of artificially generated content
has become a matter of utmost importance. The ability to create credible minute-long music …

This article tackles two major problem settings for interpretability of audio processing
networks, post-hoc and by-design interpretation. For post-hoc interpretation, we aim to …

Deep learning models have become a critical tool for analysis and classification of musical
data. These models operate either on the audio signal, eg waveform or spectrogram, or on a …

In this work, we present Score MUsic Graph (SMUG)-Explain, a framework for generating
and visualizing explanations of graph neural networks applied to arbitrary prediction tasks …

Multimodal models are critical for music understanding tasks, as they capture the complex
interplay between audio and lyrics. However, as these models become more prevalent, the …

This paper describes a data-driven framework to parse musical sequences into dependency
trees, which are hierarchical structures used in music cognition research and music …

''Why do they keep recommending me this music track?''''Why did our system recommend
these tracks to users?''Nowadays, streaming platforms are the most common way to listen to …

This article motivates, describes, and presents the PBSCR dataset for studying composer
recognition of classical piano music. Our goal was to design a dataset that facilitates large …

In breaking, which features two dancers breakdancing against each other to the rhythm of
music remixed by a disc jockey (DJ), it is important to match the technique to the timing of the …