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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 51–60 of 113 papers

TitleStatusHype
Online SuBmodular + SuPermodular (BP) Maximization with Bandit FeedbackCode0
A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System—0
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks—0
A Multi-source Graph Representation of the Movie Domain for Recommendation Dialogues Analysis—0
Integrating User and Item Reviews in Deep Cooperative Neural Networks for Movie Recommendation—0
Construction of Hierarchical Structured Knowledge-based Recommendation Dialogue Dataset and Dialogue System—0
MovieMat: Context-aware Movie Recommendation with Matrix Factorization by Matrix Fitting—0
Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation—0
VRConvMF: Visual Recurrent Convolutional Matrix Factorization for Movie Recommendation—0
Using Partial Monotonicity in Submodular Maximization—0
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