80 citations · 178 across the 9 of their papers we have counts for
11 papers
Overview and Analysis of the RecSys Challenge 2026: Conversational Music Recommendation
Seungheon Doh, Sergio Oramas, Bruno Sguerra +3
The RecSys Challenge 2026 studies conversational music recommendation as a joint item recommendation and response generation problem: given a multi-turn dialogue, systems must retr…
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…
Benchmarking Music Autotagging with MGPHot Expert Annotations vs. Generic Tag Datasets
Pedro Ramoneda, Pablo Alonso-Jiménez, Sergio Oramas +2
Music autotagging aims to automatically assign descriptive tags, such as genre, mood, or instrumentation, to audio recordings. Due to its challenges, diversity of semantic descript…
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…
Supervised and Unsupervised Learning of Audio Representations for Music Understanding
Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas +2
In this work, we provide a broad comparative analysis of strategies for pre-training audio understanding models for several tasks in the music domain, including labelling of genre,…
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…