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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

Showing 125 of 113 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
On Generative Agents in RecommendationCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of ExplanationsCode1
Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue SystemsCode1
The Adapter-Bot: All-In-One Controllable Conversational ModelCode1
INSPIRED: Toward Sociable Recommendation Dialog SystemsCode1
GHRS: Graph-based Hybrid Recommendation System with Application to Movie RecommendationCode1
LlamaRec: Two-Stage Recommendation using Large Language Models for RankingCode1
Practical 0.385-Approximation for Submodular Maximization Subject to a Cardinality ConstraintCode0
Attention-based Ingredient Phrase ParserCode0
MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender SystemsCode0
No-Regret Learning in Unknown Games with Correlated PayoffsCode0
Obeying the Order: Introducing Ordered Transfer Hyperparameter OptimisationCode0
Knowledge-aware attentional neural network for review-based movie recommendation with explanationsCode0
A Hybrid Variational Autoencoder for Collaborative FilteringCode0
LFG: A Generative Network for Real-Time RecommendationCode0
Fairness in Streaming Submodular Maximization over a Matroid ConstraintCode0
Fairness in Streaming Submodular Maximization: Algorithms and HardnessCode0
Collaborative Filtering with Recurrent Neural NetworksCode0
Online SuBmodular + SuPermodular (BP) Maximization with Bandit FeedbackCode0
Jointly Learning Propagating Features on the Knowledge Graph for Movie RecommendationCode0
BloombergGPT: A Large Language Model for FinanceCode0
Movie Recommendation System using Sentiment Analysis from Microblogging DataCode0
Bias in Knowledge Graphs -- an Empirical Study with Movie Recommendation and Different Language Editions of DBpediaCode0
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