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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 41–50 of 113 papers

TitleStatusHype
A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms—0
A Deep, Forgetful Novelty-Seeking Movie Recommender Model—0
Comprehensive Movie Recommendation System—0
Interactive Submodular Bandit—0
Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms: A Case with Bounded Regret—0
A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system—0
Language Models as Recommender Systems: Evaluations and Limitations—0
Large Language Models as Narrative-Driven Recommenders—0
Large Language Models as Recommender Systems: A Study of Popularity Bias—0
Integrating User and Item Reviews in Deep Cooperative Neural Networks for Movie Recommendation—0
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