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 32513300 of 6047 papers

TitleStatusHype
HAKG: Hierarchy-Aware Knowledge Gated Network for RecommendationCode1
Heterogeneous Acceleration Pipeline for Recommendation System Training0
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender SystemsCode1
Reinforcement Re-ranking with 2D Grid-based Recommendation Panels0
IA-GCN: Interactive Graph Convolutional Network for RecommendationCode0
Single-shot Embedding Dimension Search in Recommender System0
Introducing a Framework and a Decision Protocol to Calibrate Recommender Systems0
Musical Information Extraction from the Singing Voice0
Vertical Allocation-based Fair Exposure Amortizing in Ranking0
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative FilteringCode1
CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-AttentionCode1
Tensor Completion with Provable Consistency and Fairness Guarantees for Recommender Systems0
A Comprehensive Survey on Automated Machine Learning for Recommendations0
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender SystemCode1
ESCM^2: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate EstimationCode0
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations0
VRKG4Rec: Virtual Relational Knowledge Graphs for RecommendationCode1
Optimizing generalized Gini indices for fairness in rankings0
Entity-Centric Query Refinement0
Transformer-Empowered Content-Aware Collaborative Filtering0
Learning to Augment for Casual User Recommendation0
On the Adaptation to Concept Drift for CTR Prediction0
Sequential Recommendation with Causal Behavior Discovery0
Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation0
FedRecAttack: Model Poisoning Attack to Federated RecommendationCode1
i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender SystemsCode0
Leveraging Privacy Profiles to Empower Users in the Digital Society0
Cross-Domain Recommendation to Cold-Start Users via Variational Information BottleneckCode1
Self-Supervised Learning for Recommender Systems: A SurveyCode2
Near-optimality for infinite-horizon restless bandits with many arms0
Revisiting Neighborhood-based Link Prediction for Collaborative Filtering0
Specialized Document Embeddings for Aspect-based Similarity of Research PapersCode1
BARCOR: Towards A Unified Framework for Conversational Recommendation Systems0
Distributed data analytics0
Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data0
Data Augmentation Strategies for Improving Sequential Recommender Systems0
AutoML for Deep Recommender Systems: A Survey0
Modeling Attrition in Recommender Systems with Departing Bandits0
Movie Genre Classification by Language Augmentation and Shot SamplingCode0
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)Code2
Deep Multi-View Learning for Tire Recommendation0
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation0
Privacy-Preserving Personalized Fitness Recommender System (P3FitRec): A Multi-level Deep Learning ApproachCode0
Explainability in reinforcement learning: perspective and position0
Making Recommender Systems Forget: Learning and Unlearning for Erasable Recommendation0
Explicit User Manipulation in Reinforcement Learning Based Recommender Systems0
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI0
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations0
Meta-Learning for Online Update of Recommender SystemsCode0
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback0
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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
8GC-MCRMSE (u1 Splits)0.91Unverified
9FedPerGNNRMSE0.91Unverified
10Self-Supervised Exchangeable ModelRMSE (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
5SimpleXNDCG@200.06Unverified
6MGDCFNDCG@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
5CR-WalkerRecall@10.04Unverified
6CRFRRecall@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