Hypothesis-Driven Shelf Generation for Personalised Recommendation
From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections
Who Are We Recommending To? Recommender Systems in the Agentic Web
Contexts, Conversations & Connections: Spotify Research at RecSys 2026
Latest Publications
We publish research papers and present our work in a wide range of venues.
More publicationsThe Disconnect Between Better Descriptive Reasoning Trace Quality and Recommendation Effectiveness
Gustavo Penha, Juan Elenter Litwin, Claudia Hauff, Hugues Bouchard, Paul Bennett, Mounia Lalmas
From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections
Gustavo Penha, Aleksandr V. Petrov, Claudia Hauff, Enrico Palumbo, Ali Vardasbi, Edoardo D'Amico, Francesco Fabbri, Alice Wang, Praveen Ravichandran, Henrik Lindström, Hugues Bouchard, Mounia Lalmas
Do Sequential Recommendation Benchmarks Really Require Higher-Order Sequence Modelling?
Aleksandr V. Petrov, Praveen Ravichandran, Paul Bennett, Hugues Bouchard, Mounia Lalmas
Research Areas
How do we create more personalized experiences? What can we learn about listeners on how they use written language? How do we optimize testing methodologies? Explore all our research areas below.
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We're expanding knowledge of audio and video technology every day, sharing open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
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