From the 1 of 16 linked papers with an AI index.
16 papers
Hypothesis-Driven Shelf Generation for Personalised Recommendation
Aleksandr V. Petrov, Tarun Chillara, Matthew D. Moellman +13
The paper introduces a system for generating personalized recommendation shelves on Spotify by using natural‑language hypotheses to guide content selection, combining hypothesis ge…
As It Was: Aligning LLM Search Evaluation with Historical User Preferences
Ali Vardasbi, Gustavo Penha, Enrico Palumbo +3
Large-scale search systems evolve faster than human quality assurance can scale, especially for long-tail intents and multilingual queries. LLM-as-a-judge approaches provide a scal…
Stochastic Primal-Dual Decoding for Multiobjective Generative Recommender Systems
Dmitrii Moor, Ben Carterette, Senthilkumar Krishnamoorthy +5
Recent advances in recommender systems (RS) have shown substantial performance gains through generative modelling. In practice, recommendation often involves constructing slates --…
Primal-Dual Guided Decoding for Constrained Discrete Diffusion
Federico Tomasi, Dmitrii Moor, Alice Wang +1
Discrete diffusion models generate structured sequences by progressively unmasking tokens, but enforcing global property constraints during generation remains an open challenge. We…
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…