75 citations · 75 across the 8 of their papers we have counts for
15 papers
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…
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks
Marco De Nadai, Francesco Fabbri, Paul Gigioli +11
In the ever-evolving digital audio landscape, Spotify, well-known for its music and talk content, has recently introduced audiobooks to its vast user base. While promising, this mo…
Multi-Modal Trajectory Prediction of NBA Players
Sandro Hauri, Nemanja Djuric, Vladan Radosavljevic +1
National Basketball Association (NBA) players are highly motivated and skilled experts that solve complex decision making problems at every time point during a game. As a step towa…
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui +6
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to…
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou +5
Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potentia…