SOTAVerified

Movie Recommendation

Evaluates the ability of language models to propose relevant movie recommendations with collaborative filtering data.

Source: BIG-bench

Papers

Showing 1–10 of 113 papers

TitleStatusHype
A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms—0
LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Movie Recommendation—0
Tell Me the Good Stuff: User Preferences in Movie Recommendation Explanations—0
Multi-Selection for Recommendation Systems—0
Movie Recommendation using Web Crawling—0
Contextual Bandits with Arm Request Costs and Delays—0
Large Language Models as Narrative-Driven Recommenders—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
Ducho meets Elliot: Large-scale Benchmarks for Multimodal RecommendationCode0
Attention Overflow: Language Model Input Blur during Long-Context Missing Items Recommendation—0
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