75 citations · 820 across the 81 of their papers we have counts for
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cs.IR2024
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes
Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric +1
Recommender systems are an important part of the modern human experience whose influence ranges from the food we eat to the news we read. Yet, there is still debate as to what exte…
cs.LG2024★ 1 cited
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta +3
Offline reinforcement learning algorithms have proven effective on datasets highly connected to the target downstream task. Yet, leveraging a novel testbed (MOOD) in which trajecto…