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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 76–100 of 113 papers

TitleStatusHype
Transfer Meets Hybrid: A Synthetic Approach for Cross-Domain Collaborative Filtering with Text—0
Transforming Movie Recommendations with Advanced Machine Learning: A Study of NMF, SVD,and K-Means Clustering—0
Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank—0
Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems—0
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation—0
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
A Multi-source Graph Representation of the Movie Domain for Recommendation Dialogues Analysis—0
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies—0
Submodular Maximization in Clean Linear Time—0
A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system—0
A Survey of Point-of-interest Recommendation in Location-based Social Networks—0
Attention Overflow: Language Model Input Blur during Long-Context Missing Items Recommendation—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems—0
CherryRec: Enhancing News Recommendation Quality via LLM-driven Framework—0
Collaborative filtering via sparse Markov random fields—0
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