2 papers
cs.IR2026
Mend the Measurement Gap: Latent User Preference Modeling for Short-Form Video Recommendation
Shuo Chang, Yueqi Wang, Zihuan Diao +7
Recommender systems rely heavily on heterogeneous behavioral feedback to infer user preference. Although abundant, these signals are imperfect measurements: the same observed behav…
cs.IR2026
Breaking the Loop: An Empirical Comparison of Strategies for Novelty and Freshness in YouTube Music
Srivaths Ranganathan, Zihuan Diao, Bernardo Cunha +7
Continuously trained ranking models in music recommenders fall into feedback loops where previously consumed items dominate recommendations. This suppresses two distinct content cl…