5 citations · 6 across the 7 of their papers we have counts for
11 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…
Stream: Scaling up Mechanistic Interpretability to Long Context in LLMs via Sparse Attention
J Rosser, José Luis Redondo García, Gustavo Penha +2
As Large Language Models (LLMs) scale to million-token contexts, traditional Mechanistic Interpretability techniques for analyzing attention scale quadratically with context length…
AudioBoost: Increasing Audiobook Retrievability in Spotify Search with Synthetic Query Generation
Enrico Palumbo, Gustavo Penha, Alva Liu +6
Spotify has recently introduced audiobooks as part of its catalog, complementing its music and podcast offering. Search is often the first entry point for users to access new items…
Semantic IDs for Joint Generative Search and Recommendation
Gustavo Penha, Edoardo D'Amico, Marco De Nadai +8
Generative models powered by Large Language Models (LLMs) are emerging as a unified solution for powering both recommendation and search tasks. A key design choice in these models…
Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge
Francesco Fabbri, Gustavo Penha, Edoardo D'Amico +7
Evaluating personalized recommendations remains a central challenge, especially in long-form audio domains like podcasts, where traditional offline metrics suffer from exposure bia…
Adaptive Repetition for Mitigating Position Bias in LLM-Based Ranking
Ali Vardasbi, Gustavo Penha, Claudia Hauff +1
When using LLMs to rank items based on given criteria, or evaluate answers, the order of candidate items can influence the model's final decision. This sensitivity to item position…