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B. Sguerra

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Book Open access Sep 2026

RecSys Challenge 2026: Conversational Music Recommendation

The RecSys Challenge 2026 focuses on the evolving landscape of music discovery, where static recommendation lists are being replaced by dynamic, conversational interactions. As users increasingly interact with AI through natural language, there is a critical need for systems that can seamlessly integrate Natural Langua...

Seungheon Doh, Sergio Oramas, B. Sguerra et al. · 1 citation
#large language models Book Open access Sep 2026

Overview and Analysis of the RecSys Challenge 2026: Conversational Music Recommendation

The RecSys Challenge 2026 studies conversational music recommendation as a joint item recommendation and response generation problem: given a multi-turn dialogue, systems must retrieve relevant tracks from a large catalog and produce a grounded natural-language response. This paper presents the challenge task, dataset,...

Seungheon Doh, Sergio Oramas, B. Sguerra et al. · 0 citations
Jul 2026

LLM-as-a-Judge for Evaluating System Responses in Conversational Music Recommendation

This paper presents the first user study to empirically assess the reliability of LLM-as-a-judge for evaluating CRS responses, and finds that LLM-based judges exhibit moderate positive alignment with human assessments and outperform all reference-based baselines.

Seungheon Doh, B. Sguerra, Sergio Oramas et al. · 0 citations

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