5 citations · 8 across the 15 of their papers we have counts for
4 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…
Music Recommendation with Large Language Models: Challenges, Opportunities, and Evaluation
Elena V. Epure, Yashar Deldjoo, Bruno Sguerra +2
Music Recommender Systems (MRSs) have long relied on an information retrieval framing, where progress is measured mainly through accuracy on retrieval-oriented subtasks. While effe…
Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Alessandro B. Melchiorre, Elena V. Epure, Shahed Masoudian +4
Natural language interfaces offer a compelling approach for music recommendation, enabling users to express complex preferences conversationally. While Large Language Models (LLMs)…
Harnessing High-Level Song Descriptors towards Natural Language-Based Music Recommendation
Elena V. Epure, Gabriel Meseguer-Brocal, Darius Afchar +1
Recommender systems relying on Language Models (LMs) have gained popularity in assisting users to navigate large catalogs. LMs often exploit item high-level descriptors, i.e. categ…