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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 51–75 of 113 papers

TitleStatusHype
MTS Kion Implicit Contextualised Sequential Dataset for Movie Recommendation—0
Multi-channel Emotion Analysis for Consensus Reaching in Group Movie Recommendation Systems—0
Multi-Selection for Recommendation Systems—0
Multi-Task End-to-End Training Improves Conversational Recommendation—0
Multi-Task End-to-End Training Improves Conversational Recommendation—0
Natural Language Processing via LDA Topic Model in Recommendation Systems—0
Online Categorical Subspace Learning for Sketching Big Data with Misses—0
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks—0
PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning—0
Potential Factors Leading to Popularity Unfairness in Recommender Systems: A User-Centered Analysis—0
Provable Inductive Matrix Completion—0
RecMind: Japanese Movie Recommendation Dialogue with Seeker's Internal State—0
Sequential Item Recommendation in the MOBA Game Dota 2—0
Stability of Graph Neural Networks to Relative Perturbations—0
Streaming Submodular Maximization under a k-Set System Constraint—0
Submodular Maximization Through Barrier Functions—0
Submodular Maximization under the Intersection of Matroid and Knapsack Constraints—0
Tell Me the Good Stuff: User Preferences in Movie Recommendation Explanations—0
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization—0
Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors—0
The Informational Role of Online Recommendations: Evidence from a Field Experiment—0
User Profile Feature-Based Approach to Address the Cold Start Problem in Collaborative Filtering for Personalized Movie Recommendation—0
The Power of Subsampling in Submodular Maximization—0
Thompson Sampling for Combinatorial Semi-bandits with Sleeping Arms and Long-Term Fairness Constraints—0
Transferability Properties of Graph Neural Networks—0
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