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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
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
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