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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 31–40 of 113 papers

TitleStatusHype
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
A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System—0
DEUX: An Attribute-Guided Framework for Sociable Recommendation Dialog Systems—0
Could you guess an interesting movie from the posters?: An evaluation of vision-based features on movie poster database—0
Contextual Bandits with Arm Request Costs and Delays—0
Construction of Hierarchical Structured Knowledge-based Recommendation Dialogue Dataset and Dialogue System—0
A Survey of Point-of-interest Recommendation in Location-based Social Networks—0
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