80 citations · 161 across the 7 of their papers we have counts for
6 papers · 1 filter
LLM-as-a-Judge for Evaluating System Responses in Conversational Music Recommendation
Seungheon Doh, Bruno Sguerra, Sergio Oramas +2
Conversational Recommendation Systems (CRS) aim to achieve two primary objectives: recommending relevant items and generating natural language responses. While recommendation accur…
Contrastive Learning for Cross-modal Artist Retrieval
Andres Ferraro, Jaehun Kim, Sergio Oramas +2
Music retrieval and recommendation applications often rely on content features encoded as embeddings, which provide vector representations of items in a music dataset. Numerous com…
Artist Similarity with Graph Neural Networks
Filip Korzeniowski, Sergio Oramas, Fabien Gouyon
Artist similarity plays an important role in organizing, understanding, and subsequently, facilitating discovery in large collections of music. In this paper, we present a hybrid a…
Multimodal Metric Learning for Tag-based Music Retrieval
Minz Won, Sergio Oramas, Oriol Nieto +2
Tag-based music retrieval is crucial to browse large-scale music libraries efficiently. Hence, automatic music tagging has been actively explored, mostly as a classification task,…
A Deep Multimodal Approach for Cold-start Music Recommendation
Sergio Oramas, Oriol Nieto, Mohamed Sordo +1
An increasing amount of digital music is being published daily. Music streaming services often ingest all available music, but this poses a challenge: how to recommend new artists…
Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features
Sergio Oramas, Oriol Nieto, Francesco Barbieri +1
Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focus…