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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 21–30 of 113 papers

TitleStatusHype
Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems—0
Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems—0
LFG: A Generative Network for Real-Time RecommendationCode0
LlamaRec: Two-Stage Recommendation using Large Language Models for RankingCode1
On Generative Agents in RecommendationCode2
Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis—0
Submodular Maximization under the Intersection of Matroid and Knapsack Constraints—0
Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank—0
Obeying the Order: Introducing Ordered Transfer Hyperparameter OptimisationCode0
Fairness in Streaming Submodular Maximization over a Matroid ConstraintCode0
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