Recent advances in diffusion models and large language models have underpinned a new
generation of powerful and accessible tools, and some of the most publicly visible …

This first workshop on explainable AI for the Arts (XAIxArts) brings together a community of
researchers and creative practitioners in Human-Computer Interaction (HCI), Interaction …

Generative AI models for music and the arts in general are increasingly complex and hard to
understand. The field of explainable AI (XAI) seeks to make complex and opaque AI models …

Computationally creative systems for music have recently achieved impressive results,
fuelled by progress in generative machine learning. However, black-box approaches have …

A common musical composition practice is to develop musical pieces using variations of
musical themes. In this study, we present an interactive tool which can generate variations of …

The integration of emotion recognition capabilities within musical instruments can spur the
emergence of novel art formats and services for musicians. This paper proposes the concept …

We consider how generative AI systems could and should evolve from being used as co-
creative tools for artefact generation to co-creative collaborators for enhancing cultural …

Explaining the singability of lyrics is an important but missing ability of language models
(LMs) in song lyrics generation. This ability allows composers to quickly assess if LM …

Reflection is fundamental to creative practice. However, the plurality of ways in which people
reflect when using AI Generated Content (AIGC) is underexplored. This paper takes AI …

The incorporation of Machine and Deep Learning in Smart Healthcare technologies has
revolutionized healthcare delivery from diagnostics to treatment planning. The vast amounts …