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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
Jointly Learning Propagating Features on the Knowledge Graph for Movie RecommendationCode0
MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender SystemsCode0
Bias in Knowledge Graphs -- an Empirical Study with Movie Recommendation and Different Language Editions of DBpediaCode0
Harm Mitigation in Recommender Systems under User Preference DynamicsCode0
Knowledge-aware attentional neural network for review-based movie recommendation with explanationsCode0
Obeying the Order: Introducing Ordered Transfer Hyperparameter OptimisationCode0
ExCalibR: Expected Calibration of Recommendations—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation—0
Attention Overflow: Language Model Input Blur during Long-Context Missing Items Recommendation—0
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