SOTAVerified

Recommendation Systems

Recommendation System in AI Research

A Recommendation System is a specialized AI-driven model that analyzes user preferences and behaviors to suggest relevant content, products, or services. It is widely used in domains like e-commerce, streaming platforms, social media, and personalized learning.

AI research in recommendation systems focuses on:

  • Collaborative Filtering: Predicting user preferences based on similar users' choices.
  • Content-Based Filtering: Recommending items based on user history and item characteristics.
  • Hybrid Models: Combining multiple techniques for better accuracy.
  • Deep Learning & Transformers: Using neural networks and self-attention mechanisms for personalized recommendations.
  • Graph-Based Approaches: Leveraging knowledge graphs for relationship-aware recommendations.

Key challenges include data sparsity, scalability, and bias mitigation. Cutting-edge research explores reinforcement learning, explainability, and privacy-preserving methods to enhance recommendation systems.

Papers

Showing 10511100 of 6047 papers

TitleStatusHype
Personalized Multi-task Training for Recommender System0
Powerful A/B-Testing Metrics and Where to Find Them0
GradCraft: Elevating Multi-task Recommendations through Holistic Gradient CraftingCode0
Adaptive Utilization of Cross-scenario Information for Multi-scenario Recommendation0
Fusion Self-supervised Learning for Recommendation0
A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation0
Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components RecommendationCode0
AOTree: Aspect Order Tree-based Model for Explainable Recommendation0
Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insights0
Interpretable Triplet Importance for Personalized RankingCode0
MaTrRec: Uniting Mamba and Transformer for Sequential RecommendationCode0
Conversational Dueling Bandits in Generalized Linear ModelsCode0
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient RecommendationCode1
IntentRec: Predicting User Session Intent with Hierarchical Multi-Task Learning0
Assessing AI Utility: The Random Guesser Test for Sequential Decision-Making Systems0
Intent-guided Heterogeneous Graph Contrastive Learning for RecommendationCode1
Pareto Front Approximation for Multi-Objective Session-Based Recommender SystemsCode3
TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou0
Flexible Generation of Preference Data for Recommendation AnalysisCode0
Leveraging LLM Reasoning Enhances Personalized Recommender Systems0
Low Rank Field-Weighted Factorization Machines for Low Latency Item RecommendationCode0
Deep Uncertainty-Based Explore for Index Construction and Retrieval in Recommendation System0
Scalable Dynamic Embedding Size Search for Streaming Recommendation0
Dual Test-time Training for Out-of-distribution Recommender System0
Retrieval with Learned SimilaritiesCode2
LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme0
Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models0
User-Creator Feature Polarization in Recommender Systems with Dual Influence0
Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income CommunitiesCode1
Knowledge Distillation Approaches for Accurate and Efficient Recommender SystemCode1
Frontiers of Deep Learning: From Novel Application to Real-World Deployment0
Capturing Style in Author and Document Representation0
A Comprehensive Review of Recommender Systems: Transitioning from Theory to PracticeCode1
Differential Privacy Mechanisms in Neural Tangent Kernel Regression0
Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMMCode0
MLSA4Rec: Mamba Combined with Low-Rank Decomposed Self-Attention for Sequential Recommendation0
On Causally Disentangled State Representation Learning for Reinforcement Learning based Recommender Systems0
Evaluating the performance-deviation of itemKNN in RecBole and LensKit0
ROLeR: Effective Reward Shaping in Offline Reinforcement Learning for Recommender SystemsCode0
Watermarking Recommender SystemsCode0
Temporal receptive field in dynamic graph learning: A comprehensive analysisCode0
GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal RecommendationCode1
Evaluating graph-based explanations for AI-based recommender systems0
Graph Signal Processing for Cross-Domain RecommendationCode0
NudgeRank: Digital Algorithmic Nudging for Personalized Health0
Characterizing and Understanding HGNN Training on GPUs0
E-Commerce Product Recommendation System based on ML Algorithms0
Efficient Continual Learning with Low Memory Footprint For Edge Device0
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation0
UET4Rec: U-net Encapsulated Transformer for Sequential RecommenderCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KTUP (soft)HR@100.89Unverified
2Factorization with dictionary learningRMSE0.87Unverified
3Factorized EAERMSE0.86Unverified
4U-CFNRMSE0.86Unverified
5IGMCRMSE0.86Unverified
6FedGNNRMSE0.85Unverified
7NNMFRMSE0.84Unverified
8BSTRMSE0.84Unverified
9FedPerGNNRMSE0.84Unverified
10GHRSRMSE0.84Unverified
#ModelMetricClaimedVerifiedStatus
1LT-OCFRecall@200.19Unverified
2SSCFnDCG@200.06Unverified
3SANSAnDCG@200.06Unverified
4RLAE-DANnDCG@200.06Unverified
5HSTU+MoLHR@100.06Unverified
6BSPM-LMnDCG@200.06Unverified
7BSPM-EMnDCG@200.06Unverified
8Turbo-CFnDCG@200.06Unverified
9Emb-GCNnDCG@200.06Unverified
10NESCLnDCG@200.05Unverified
#ModelMetricClaimedVerifiedStatus
1GMCRMSE (u1 Splits)1Unverified
2GRALSRMSE (u1 Splits)0.95Unverified
3sRGCNNRMSE (u1 Splits)0.93Unverified
4WMLFFRMSE (u1 Splits)0.93Unverified
5FedGNNRMSE0.92Unverified
6Factorized EAERMSE (u1 Splits)0.92Unverified
7GRAEM / KPMFRMSE (u1 Splits)0.92Unverified
8Self-Supervised Exchangeable ModelRMSE (u1 Splits)0.91Unverified
9FedPerGNNRMSE0.91Unverified
10GC-MCRMSE (u1 Splits)0.91Unverified
#ModelMetricClaimedVerifiedStatus
1HyperMLnDCG@100.64Unverified
2LRMLnDCG@100.62Unverified
3CMLnDCG@100.53Unverified
4Multi-Gradient DescentRecall@200.42Unverified
5RecVAERecall@200.41Unverified
6VASPRecall@200.41Unverified
7H+Vamp GatedRecall@200.41Unverified
8RaCTRecall@200.4Unverified
9Mult-VAE PRRecall@200.4Unverified
10EASERecall@200.39Unverified
#ModelMetricClaimedVerifiedStatus
1U-RBMRMSE0.82Unverified
2FedGNNRMSE0.8Unverified
3Factorization with dictionary learningRMSE0.8Unverified
4U-CFNRMSE0.8Unverified
5FedPerGNNRMSE0.79Unverified
6I-AutoRecRMSE0.78Unverified
7GC-MCRMSE0.78Unverified
8I-CFNRMSE0.78Unverified
9SGD MFRMSE0.77Unverified
10CF-NADERMSE0.77Unverified
#ModelMetricClaimedVerifiedStatus
1ConvNCFnDCG@200.6Unverified
2NESCLnDCG@200.16Unverified
3RLAE-DANnDCG@200.16Unverified
4BSPM-EMnDCG@200.16Unverified
5MGDCFnDCG@200.16Unverified
6Emb-GCNnDCG@200.16Unverified
7LT-OCFnDCG@200.16Unverified
8BSPM-LMnDCG@200.16Unverified
9SimpleXnDCG@200.16Unverified
10LightGCNnDCG@200.16Unverified
#ModelMetricClaimedVerifiedStatus
1NESCLNDCG@200.06Unverified
2BSPM-EMNDCG@200.06Unverified
3RLAE-DANNDCG@200.06Unverified
4BSPM-LMNDCG@200.06Unverified
5MGDCFNDCG@200.06Unverified
6SimpleXNDCG@200.06Unverified
7Turbo-CFNDCG@200.06Unverified
8LT-OCFNDCG@200.05Unverified
9SSCFNDCG@200.05Unverified
10LightGCNNDCG@200.05Unverified
#ModelMetricClaimedVerifiedStatus
1H+Vamp GatednDCG@1000.41Unverified
2RecVAEnDCG@1000.39Unverified
3EASEnDCG@1000.39Unverified
4RaCTnDCG@1000.39Unverified
5Mult-VAE PRnDCG@1000.39Unverified
6Mult-DAEnDCG@1000.38Unverified
7∞-AEnDCG@1000.37Unverified
8LRMLnDCG@100.36Unverified
9CMLnDCG@100.29Unverified
10RATE-CSERecall@100.2Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE0.83Unverified
2sRGCNNRMSE0.8Unverified
3Factorized EAERMSE0.74Unverified
4GC-MCRMSE0.73Unverified
5GRAEM / KPMFRMSE0.73Unverified
6MG-GATRMSE0.73Unverified
7IGMCRMSE0.72Unverified
8GLocal-KRMSE0.72Unverified
#ModelMetricClaimedVerifiedStatus
1UCCRRecall@100.22Unverified
2KERLRecall@10.06Unverified
3C2CRSRecall@10.05Unverified
4UniCRSRecall@10.05Unverified
5CRFRRecall@10.04Unverified
6CR-WalkerRecall@10.04Unverified
7KGSFRecall@10.04Unverified
8KBRDRecall@10.03Unverified
#ModelMetricClaimedVerifiedStatus
1CARCA Abs + ConHit@100.68Unverified
2ProxyRCAHit@100.63Unverified
3CARCA-RotatoryHit@100.62Unverified
4CARCAHit@100.58Unverified
5SSE-PTHit@100.5Unverified
6SASRecHit@100.49Unverified
7HetroFairMAP@200.14Unverified
#ModelMetricClaimedVerifiedStatus
1∞-AEAUC0.95Unverified
2FedGNNRMSE0.79Unverified
3FedPerGNNRMSE0.78Unverified
4GRALSRMSE0.71Unverified
5U-CFNRMSE0.7Unverified
6I-CFNRMSE0.69Unverified
7DGRecNDCG0.2Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE1.24Unverified
2sRGCNNRMSE0.93Unverified
3GC-MCRMSE0.92Unverified
4Factorized EAERMSE0.91Unverified
5GRAEMRMSE0.89Unverified
6MG-GATRMSE0.88Unverified
7IGMCRMSE0.87Unverified
#ModelMetricClaimedVerifiedStatus
1EASEnDCG@1000.39Unverified
2SANSAnDCG@1000.39Unverified
3RecVAEnDCG@1000.33Unverified
4RaCTnDCG@1000.32Unverified
5Mult-VAE PRnDCG@1000.32Unverified
6Mult-DAEnDCG@1000.31Unverified
7CMLRecall@500.25Unverified
#ModelMetricClaimedVerifiedStatus
1TLSANAUC0.95Unverified
2ProxyRCAHit@100.81Unverified
3CARCA-Rotatory + Con.Hit@100.81Unverified
4CARCAHit@100.78Unverified
5SSE-PTHit@100.78Unverified
6SASRecHit@100.74Unverified
#ModelMetricClaimedVerifiedStatus
1GRALSRMSE38.04Unverified
2sRGCNNRMSE22.41Unverified
3GC-MCRMSE20.5Unverified
4Factorized EAERMSE20Unverified
5IGMCRMSE19.1Unverified
6MG-GATRMSE18.9Unverified
#ModelMetricClaimedVerifiedStatus
1SAERSAUC0.82Unverified
2RMHA-4Hit@100.77Unverified
3ProxyRCAHitRatio@ 10 (100 Neg. Samples)0.66Unverified
4CARCAHitRatio@ 10 (100 Neg. Samples)0.59Unverified
#ModelMetricClaimedVerifiedStatus
1GraphRecMAE0.82Unverified
2NSCR (Wang et al., 2017)MAE0.8Unverified
3DANSERMAE0.78Unverified
4HetroFairMAP@200.04Unverified