5 papers
Efficient Dataset Selection for Continual Adaptation of Generative Recommenders
Cathy Jiao, Juan Elenter, Praveen Ravichandran +7
Recommendation systems must continuously adapt to evolving user behavior, yet the volume of data generated in large-scale streaming environments makes frequent full retraining impr…
Deploying Semantic ID-based Generative Retrieval for Large-Scale Podcast Discovery at Spotify
Edoardo D'Amico, Marco De Nadai, Praveen Chandar +41
Podcast listening is often grounded in a set of favorite shows, while listener intent can evolve over time. This combination of stable preferences and changing intent motivates rec…
A Unified Language Model for Large Scale Search, Recommendation, and Reasoning
Marco De Nadai, Edoardo D'Amico, Max Lefarov +18
LLMs are increasingly applied to recommendation, retrieval, and reasoning, yet deploying a single end-to-end model that can jointly support these behaviors over large, heterogeneou…
Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models
Bernd Huber, Ghazal Fazelnia, Andreas Damianou +6
Large language models (LLMs) excel at generating contextually relevant content. However, tailoring these outputs to individual users for effective personalization is a significant…
PODTILE: Facilitating Podcast Episode Browsing with Auto-generated Chapters
Azin Ghazimatin, Ekaterina Garmash, Gustavo Penha +14
Listeners of long-form talk-audio content, such as podcast episodes, often find it challenging to understand the overall structure and locate relevant sections. A practical solutio…