27 citations · 55 across the 9 of their papers we have counts for
3 papers · 1 filter
Augment, Drop & Swap: Improving Diversity in LLM Captions for Efficient Music-Text Representation Learning
Ilaria Manco, Justin Salamon, Oriol Nieto
Audio-text contrastive models have become a powerful approach in music representation learning. Despite their empirical success, however, little is known about the influence of key…
Foundation Models for Music: A Survey
Yinghao Ma, Anders Øland, Anton Ragni +39
In recent years, foundation models (FMs) such as large language models (LLMs) and latent diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This com…
MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models
Benno Weck, Ilaria Manco, Emmanouil Benetos +3
Multimodal models that jointly process audio and language hold great promise in audio understanding and are increasingly being adopted in the music domain. By allowing users to que…