MovieLens
Canonical152papers using it
2007first seen
Movie-rating datasets (100K–25M ratings) — the standard recommender-systems benchmark.
Papers using MovieLens (152)
- Contrastive Learning for Cold Start Recommendation with Adaptive Feature
FusionEnhancing User Intent for Recommendation Systems via Large Language
ModelsSTARec: An Efficient Agent Framework for Recommender Systems via Autonomous Deliberate ReasoningDifferentiable Fuzzy Neural Networks for Recommender SystemsBeyond Relevance: An Adaptive Exploration-Based Framework for
Personalized RecommendationsA Serendipitous Recommendation System Considering User CuriosityFACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for
Enabling Fair LLM-Based Recommender SystemsVectorized Context-Aware Embeddings for GAT-Based Collaborative FilteringModel-agnostic post-hoc explainability for recommender systemsMeta-Learning for Cold-Start Personalization in Prompt-Tuned LLMsIntegrating LLM-Derived Multi-Semantic Intent into Graph Model for Session-based RecommendationDistance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical RecommendationEnhancing LLM-based Recommendation through Semantic-Aligned
Collaborative KnowledgeLusifer: LLM-based User SImulated Feedback Environment for online Recommender systemsKGRec: A knowledge graph attention-based model for recommender systemRank-Constrained Deep Matrix Completion for Group RecommendationSAILRec: Steering LLM Attention to Dual-Side Semantically Aligned Collaborative Embeddings for RecommendationFASR: A Future-Aware and Smooth Rhythm-Aware Time-Gated GRU for Sequential RecommendationAdaptive weighting-based hybrid recommender system: self-learning adaptive recommendation (SL-ARec)An adversarial framework with dual genetic optimization for similarity-aware matrix factorization in recommendation systemsFirst, do no harm: Breaking suicidogenic echo chambers in media recommendationModeling User Exploration Saturation: When Recommender Systems Should Stop Pushing NoveltyGraphRAG-IRL: Personalized Recommendation with Graph-Grounded Inverse Reinforcement Learning and LLM Re-rankingCASP: Support-Aware Offline Policy Selection for Two-Stage Recommender SystemsCombating data scarcity in recommendation services: Integrating cognitive types of VARK and neural network technologies (LLM)R3-REC: Reasoning-Driven Recommendation via Retrieval-Augmented LLMs over Multi-Granular Interest SignalsScalable Sequential Recommendation under Latency and Memory ConstraintsExplaining Group Recommendations via CounterfactualsBERT and CNN integrated Neural Collaborative Filtering for Recommender SystemsWeightless Neural Networks for Continuously Trainable Personalized Recommendation SystemsHyMoERec: Hybrid Mixture-of-Experts for Sequential RecommendationEnhancing Group Recommendation using Soft Impute Singular Value DecompositionMembership Inference Attack against Large Language Model-based Recommendation Systems: A New Distillation-based ParadigmFidelity-Aware Recommendation Explanations via Stochastic Path IntegrationPrivacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender SystemsAgenticRAG: Tool-Augmented Foundation Models for Zero-Shot Explainable Recommender SystemsCTRL-Rec: Controlling Recommender Systems With Natural LanguageFrom Time and Place to Preference: LLM-Driven Geo-Temporal Context in RecommendationsDataset Pruning in RecSys and ML: Best Practice or Mal-Practice?End-to-End Personalization: Unifying Recommender Systems with Large Language ModelsCollaborative Filtering using Variational Quantum Hopfield Associative MemoryChurn-Aware Recommendation Planning under Aggregated Preference FeedbackRecRankerEval: A Flexible and Extensible Framework for Top-k LLM-based RecommendationDUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie RecommendationMoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert SpecializationEnhancing Live Broadcast Engagement: A Multi-modal Approach to Short Video Recommendations Using MMGCN and User PreferencesHI-Series Algorithms A Hybrid of Substance Diffusion Algorithm and
Collaborative FilteringRecommendation and TemptationCFaiRLLM: Consumer Fairness Evaluation in Large-Language Model
Recommender SystemLatent Relational Metric Learning via Memory-based Attention for
Collaborative RankingFederated Collaborative Filtering for Privacy-Preserving Personalized
Recommendation SystemContext-aware Sequential RecommendationGHRS: Graph-based Hybrid Recommendation System with Application to Movie
RecommendationRetaGNN: Relational Temporal Attentive Graph Neural Networks for
Holistic Sequential RecommendationRegularizing Matrix Factorization with User and Item Embeddings for
RecommendationMVIN: Learning Multiview Items for RecommendationGLocal-K: Global and Local Kernels for Recommender SystemsItem-side Fairness of Large Language Model-based Recommendation SystemHierarchical Context enabled Recurrent Neural Network for RecommendationDeep Heterogeneous Autoencoders for Collaborative FilteringPopularity Bias in Collaborative Filtering-Based Multimedia Recommender
SystemsHybrid Collaborative Filtering with AutoencodersMeasuring Recommender System Effects with Simulated UsersExploring Deep Space: Learning Personalized Ranking in a Semantic SpaceA Random Walk Based Model Incorporating Social Information for RecommendationsCollaborative Recommendation Model Based on Multi-modal Multi-view
Attention Network: Movie and literature casesSemi-metric networks for recommender systemsCollaborative Filtering with User-Item Co-Autoregressive ModelsA Hybrid Variational Autoencoder for Collaborative FilteringLLMRec: Large Language Models with Graph Augmentation for RecommendationOne-at-a-time: A Meta-Learning Recommender-System for
Recommendation-Algorithm Selection on Micro LevelBilateral Self-unbiased Learning from Biased Implicit FeedbackGenerative Sequential Recommendation with GPTRecRecommending Items in Social Tagging Systems Using Tag and Time InformationCUPCF: Combining Users Preferences in Collaborative Filtering for Better
RecommendationEnhancing VAEs for Collaborative Filtering: Flexible Priors & Gating
MechanismsPrivacy Preserving Recommendation System Based on GroupsAn FCA-based Boolean Matrix Factorisation for Collaborative FilteringTop-N-Rank: A Scalable List-wise Ranking Method for Recommender SystemsEmbedding Ranking-Oriented Recommender System GraphsUP5: Unbiased Foundation Model for Fairness-aware RecommendationStronger Privacy for Federated Collaborative Filtering with Implicit
FeedbackA new system-wide diversity measure for recommendations with efficient
algorithmsDeep Reinforcement Learning based Group Recommender SystemA Scalable Recommendation Engine for New Users and ItemsCold-start Problems in Recommendation Systems via Contextual-bandit AlgorithmsTop-N recommendations in the presence of sparsity: An NCD-based approachAttention-based Mixture Density Recurrent Networks for History-based
RecommendationLatent Factor Interpretations for Collaborative FilteringOn hybrid modular recommendation systems for video streamingdiv2vec: Diversity-Emphasized Node EmbeddingWhen are recommender systems useful?Wasserstein Autoencoders for Collaborative FilteringLink Prediction in Dynamic Graphs for RecommendationImproving Recommendation Diversity by Highlighting the ExTrA Fabricated
ExpertsHybrid Movie Recommender System based on Resource AllocationAttention-Based Recommendation On GraphsOn Generative Agents in RecommendationRAPS: A Recommender Algorithm Based on Pattern StructuresHow robust is MovieLens? A dataset analysis for recommender systemsEcho Chambers in Collaborative Filtering Based Recommendation SystemsMulti-Task End-to-End Training Improves Conversational RecommendationKnowledge Graph Driven Recommendation System AlgorithmRethinking Large Language Model Architectures for Sequential
RecommendationsThe MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online
Recommender SystemsSimultaneous Unlearning of Multiple Protected User Attributes From
Variational Autoencoder Recommenders Using Adversarial TrainingA two-step Recommendation Algorithm via Iterative Local Least SquaresInformation Filtering via Balanced Diffusion on Bipartite NetworksConsistence beats causality in recommender systemsAdversarial Collaborative Auto-encoder for Top-N RecommendationDeep Item-based Collaborative Filtering for Top-N RecommendationNeural Fair Collaborative FilteringModurec: Recommender Systems with Feature and Time ModulationLearning Similarity Preserving Binary Codes for Recommender SystemsRecFusion: A Binomial Diffusion Process for 1D Data for RecommendationCross-Attribute Matrix Factorization Model with Shared User EmbeddingMovie Recommendation with Poster Attention via Multi-modal Transformer
Feature FusionLLM-KT: A Versatile Framework for Knowledge Transfer from Large Language
Models to Collaborative FilteringConquering the rating bound problem in neighborhood-based collaborative filtering: a function recovery approachMulti-Linear Interactive Matrix FactorizationBinary Latent Representations for Efficient Ranking: Empirical
AssessmentA Fuzzy Community-Based Recommender System Using PageRankTowards Comprehensive Recommender Systems: Time-Aware
UnifiedcRecommendations Based on Listwise Ranking of Implicit Cross-Network
DataD2RLIR : an improved and diversified ranking function in interactive
recommendation systems based on deep reinforcement learningAn Adaptive Hybrid Active Learning Strategy with Free Ratings in
Collaborative FilteringMulti-Auxiliary Augmented Collaborative Variational Auto-encoder for Tag
RecommendationMTS Kion Implicit Contextualised Sequential Dataset for Movie
RecommendationPrivMVMF: Privacy-Preserving Multi-View Matrix Factorization for
Recommender SystemsA Two Step Approach to Weighted Bipartite Link RecommendationsImproving Sequential Recommendation Models with an Enhanced Loss
FunctionNeighbor Based Enhancement for the Long-Tail Ranking Problem in Video
Rank ModelsExplaining the Performance of Collaborative Filtering Methods With
Optimal Data CharacteristicsUser-Controllable Recommendation via Counterfactual Retrospective and
Prospective ExplanationsDynamic Collaborative Filtering for Matrix- and Tensor-based Recommender
SystemsLanguage-Based User Profiles for RecommendationPlay to Your Strengths: Collaborative Intelligence of Conventional
Recommender Models and Large Language ModelsA Normative Framework for Benchmarking Consumer Fairness in Large
Language Model Recommender SystemImprove Temporal Awareness of LLMs for Sequential RecommendationPolyhedral Conic Classifier for CTR PredictionUserSumBench: A Benchmark Framework for Evaluating User Summarization
ApproachesMultilingual Prompts in LLM-Based Recommenders: Performance Across
LanguagesContext-aware adaptive personalised recommendation: a meta-hybridMetamorphic Evaluation of ChatGPT as a Recommender SystemPersonalized Recommendation via Integrated Diffusion on User-Item-Tag Tripartite GraphsSolving the Cold-Start Problem in Recommender Systems with Social TagsInformation Filtering via Collaborative User Clustering ModelingUltra accurate collaborative information filtering via directed user similarityA vertex similarity index for better personalized recommendationDiffusion-like recommendation with enhanced similarity of objectsEigenRec: Generalizing PureSVD for Effective and Efficient Top-N RecommendationsNeural Representations in Hybrid Recommender Systems: Prediction versus
RegularizationUnlearning Protected User Attributes in Recommendations with Adversarial
Training