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Movie Recommendation

Evaluates the ability of language models to propose relevant movie recommendations with collaborative filtering data.

Source: BIG-bench

Papers

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Showing 81–90 of 113 papers

TitleStatusHype
Submodular Maximization Through Barrier Functions—0
Streaming Submodular Maximization under a k-Set System ConstraintCode0
Leveraging Long and Short-Term Information in Content-Aware Movie Recommendation via Adversarial Training—0
Streaming Submodular Maximization under a k-Set System Constraint—0
Stability of Graph Neural Networks to Relative Perturbations—0
Natural Language Processing via LDA Topic Model in Recommendation Systems—0
No-Regret Learning in Unknown Games with Correlated PayoffsCode0
A Deep, Forgetful Novelty-Seeking Movie Recommender Model—0
User Profile Feature-Based Approach to Address the Cold Start Problem in Collaborative Filtering for Personalized Movie Recommendation—0
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization—0
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