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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
Using Partial Monotonicity in Submodular Maximization—0
Using Shortlists to Support Decision Making and Improve Recommender System Performance—0
VRConvMF: Visual Recurrent Convolutional Matrix Factorization for Movie Recommendation—0
Wide and Deep Graph Neural Network with Distributed Online Learning—0
Thematic recommendations on knowledge graphs using multilayer networks—0
A case study of Empirical Bayes in User-Movie Recommendation system—0
A Deep, Forgetful Novelty-Seeking Movie Recommender Model—0
A Fairness-aware Hybrid Recommender System—0
A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms—0
A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System—0
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