SPADE: Escaping the Popularity-Similarity Frontier to Measure Serendipitous Recommendations

arXiv:2609.31164 · cs.IR, cs.AI, cs.LG · Submitted 2026-09-25 · Read on arXiv

cs.IR, cs.AI, cs.LG

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/Maarten11/SPADE

Project page: https://tobiasvente.github.io

Terminology

• Accuracy — 22× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Point-wise Mutual Information — 2× in this paper
• ACM Transactions on Intelligent Systems and Technology — 1× in this paper
• Active Exploration — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Multi-objective Optimization — 1× in this paper · explained in 4 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Deep Pareto Reinforcement Learning for Multi-Objective Recommender Systems
• How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

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