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Cited By

Let's Get It Started: Fostering the Discoverability of New Releases on
Deezer

Let's Get It Started: Fostering the Discoverability of New Releases on Deezer

5 January 2024

Théo Bontempelli

François Rigaud

Benjamin Chapus

Thomas Bouabça

Guillaume Salha-Galvan

ArXiv (abs)PDF HTML

Papers citing "Let's Get It Started: Fostering the Discoverability of New Releases on Deezer"

5 / 5 papers shown

"Beyond the past": Leveraging Audio and Human Memory for Sequential Music Recommendation

"Beyond the past": Leveraging Audio and Human Memory for Sequential Music RecommendationACM Conference on Recommender Systems (RecSys), 2025

Gabriel Meseguer-Brocal

Manuel Moussallam

273

0

0

23 Jul 2025

Optimal Baseline Corrections for Off-Policy Contextual Bandits

Optimal Baseline Corrections for Off-Policy Contextual BanditsACM Conference on Recommender Systems (RecSys), 2024

Harrie Oosterhuis

Maarten de Rijke

278

11

0

09 May 2024

Multi-Objective Recommendation via Multivariate Policy Learning

Multi-Objective Recommendation via Multivariate Policy LearningACM Conference on Recommender Systems (RecSys), 2024

Aleksei Ustimenko

235

10

0

03 May 2024

Exploring the Impact of Large Language Models on Recommender Systems: An
Extensive Review

Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review

Vinija Jain

284

22

0

11 Feb 2024

Billion-scale similarity search with GPUs

Billion-scale similarity search with GPUsIEEE Transactions on Big Data (TBD), 2017

977

4,561

0

28 Feb 2017