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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
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
A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms—0
A Deep, Forgetful Novelty-Seeking Movie Recommender Model—0
Comprehensive Movie Recommendation System—0
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