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Found 6 papers, 1 papers with code
Towards Graph Foundation Models for Personalization
In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions.
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks
While promising, this move presents significant challenges for personalized recommendations.
Improving Content Retrievability in Search with Controllable Query Generation
A pre-requisite to discover an entity, e. g. a book, with a search engine is that the entity is retrievable, i. e. there are queries for which the system will surface such entity in the top results.
Episodes Discovery Recommendation with Multi-Source Augmentations
Recommender systems (RS) commonly retrieve potential candidate items for users from a massive number of items by modeling user interests based on historical interactions.
Sequential Recommendation via Stochastic Self-Attention
We further argue that BPR loss has no constraint on positive and sampled negative items, which misleads the optimization.
Trajectory Based Podcast Recommendation
Podcast recommendation is a growing area of research that presents new challenges and opportunities.
