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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 1–50 of 113 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
On Generative Agents in RecommendationCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue SystemsCode1
GHRS: Graph-based Hybrid Recommendation System with Application to Movie RecommendationCode1
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of ExplanationsCode1
INSPIRED: Toward Sociable Recommendation Dialog SystemsCode1
The Adapter-Bot: All-In-One Controllable Conversational ModelCode1
LlamaRec: Two-Stage Recommendation using Large Language Models for RankingCode1
Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship—0
A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms—0
A Survey of Point-of-interest Recommendation in Location-based Social Networks—0
A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
A Deep, Forgetful Novelty-Seeking Movie Recommender Model—0
Modeling and Utilizing User's Internal State in Movie Recommendation Dialogue—0
Linear Bandit Algorithms with Sublinear Time Complexity—0
Submodular Maximization in Clean Linear Time—0
Collaborative filtering via sparse Markov random fields—0
A case study of Empirical Bayes in User-Movie Recommendation system—0
A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system—0
Leveraging Offline Data in Linear Latent Bandits—0
Construction of Hierarchical Structured Knowledge-based Recommendation Dialogue Dataset and Dialogue System—0
Contextual Bandits with Arm Request Costs and Delays—0
Could you guess an interesting movie from the posters?: An evaluation of vision-based features on movie poster database—0
DEUX: An Attribute-Guided Framework for Sociable Recommendation Dialog Systems—0
Attention Overflow: Language Model Input Blur during Long-Context Missing Items Recommendation—0
Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation—0
ExCalibR: Expected Calibration of Recommendations—0
Exponential Family Embeddings—0
Leveraging Long and Short-term Information in Content-aware Movie Recommendation—0
CherryRec: Enhancing News Recommendation Quality via LLM-driven Framework—0
Graph and graphon neural network stability—0
Break Out of a Pigeonhole: A Unified Framework for Examining Miscalibration, Bias, and Stereotype in Recommender Systems—0
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies—0
Fast Distributed Submodular Cover: Public-Private Data Summarization—0
Greed is Good: Near-Optimal Submodular Maximization via Greedy Optimization—0
Group Movie Selection using Multi-channel Emotion Recognition—0
A Fairness-aware Hybrid Recommender System—0
I know why you like this movie: Interpretable Efficient Multimodal Recommender—0
Learning Data Teaching Strategies Via Knowledge Tracing—0
Integrating User and Item Reviews in Deep Cooperative Neural Networks for Movie Recommendation—0
Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms: A Case with Bounded Regret—0
Interactive Submodular Bandit—0
Comprehensive Movie Recommendation System—0
Leveraging Long and Short-Term Information in Content-Aware Movie Recommendation via Adversarial Training—0
Language Models as Recommender Systems: Evaluations and Limitations—0
Large Language Models as Narrative-Driven Recommenders—0
Large Language Models as Recommender Systems: A Study of Popularity Bias—0
A Multi-source Graph Representation of the Movie Domain for Recommendation Dialogues Analysis—0
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