From Models to Products: LLMs for Recommendation at Spotify Scale
Balancing Multiple Objectives in Generative Recommendations with Adaptive Decoding
Cold-Starting Podcast Ads with Multi-Task Learning
Transforming AI Research into Personalized Listening: Spotify at NeurIPS 2025
Latest Publications
We publish research papers and present our work in a wide range of venues.
More publicationsFrom Habits to Discovery: Deploying LLMs for Personalized Generative Recommendations at Spotify
Reid Wilbur, Tarun Chillara, Vladan Radosavljevic, Pooja Chitkara, Sainath Adapa, Juan Elenter, Bernd Huber, Jacqueline Wood, Saaketh Vedantam, Jan Stypka, Sandeep Ghael, Martin D. Gould, David Murgatroyd, Yves Raimond, Mounia Lalmas, Paul N. Bennett
A Unified Model for Personalization: Language-Steerable Generative Recommendation, Search, and User Understanding
Shawn Lin, Jacqueline Wood, Jan Stypka, Eliza Klyce, Keshi Dai, Matthew N.K. Smith, Timothy Heath, Martin D. Gould, Yves Raimond, Sandeep Ghael, Tony Jebara, Andreas Damianou, Vladan Radosavljevic, Paul Bennett, Mounia Lalmas, Praveen Chandar
Stochastic Primal-Dual Decoding for Multiobjective Generative Recommender Systems
Dmitrii Moor, Ben Carterette, Senthilkumar Krishnamoorthy, Kyle Kretschman, Denis Beslic, Melissa Yalla, Alice Y Wang, 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.
We are looking for pioneers to join us in all research areas
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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