SOTAVerified

Click-Through Rate Prediction

Click-through rate prediction is the task of predicting the likelihood that something on a website (such as an advertisement) will be clicked.

( Image credit: Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction )

Papers

Showing 201250 of 391 papers

TitleStatusHype
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding0
Leaf-FM: A Learnable Feature Generation Factorization Machine for Click-Through Rate Prediction0
Learning a Product Relevance Model from Click-Through Data in E-Commerce0
Learning Representations of Categorical Feature Combinations via Self-Attention0
Learn over Past, Evolve for Future: Search-based Time-aware Recommendation with Sequential Behavior Data0
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation0
LIBER: Lifelong User Behavior Modeling Based on Large Language Models0
Light-weight End-to-End Graph Interest Network for CTR Prediction in E-commerce Search0
LiRank: Industrial Large Scale Ranking Models at LinkedIn0
LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions0
Look into the Future: Deep Contextualized Sequential Recommendation0
NCS4CVR: Neuron-Connection Sharing for Multi-Task Learning in Video Conversion Rate Prediction0
Making the Full Model Adaptive: Multi-level Domain Adaptation for Multi-Domain CTR Prediction0
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer0
MetaSplit: Meta-Split Network for Limited-Stock Product Recommendation0
Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction0
MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling0
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction0
Mitigate Position Bias with Coupled Ranking Bias on CTR Prediction0
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction0
MMBAttn: Max-Mean and Bit-wise Attention for CTR Prediction0
Moment&Cross: Next-Generation Real-Time Cross-Domain CTR Prediction for Live-Streaming Recommendation at Kuaishou0
MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction0
Multi-Epoch Learning for Deep Click-Through Rate Prediction Models0
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction0
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction0
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System0
Mutual Learning for Finetuning Click-Through Rate Prediction Models0
NeSHFS: Neighborhood Search with Heuristic-based Feature Selection for Click-Through Rate Prediction0
News Popularity Beyond the Click-Through-Rate for Personalized Recommendations0
On-Device Model Fine-Tuning with Label Correction in Recommender Systems0
One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction0
Online Interaction Detection for Click-Through Rate Prediction0
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction0
On the Practice of Deep Hierarchical Ensemble Network for Ad Conversion Rate Prediction0
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction0
PBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System0
PHN: Parallel heterogeneous network with soft gating for CTR prediction0
Polyhedral Conic Classifier for CTR Prediction0
PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction0
PRECTR: A Synergistic Framework for Integrating Personalized Search Relevance Matching and CTR Prediction0
Predict Click-Through Rates with Deep Interest Network Model in E-commerce Advertising0
Predicting clicks in online display advertising with latent features and side-information0
Provable Sparse Tensor Decomposition0
RBoard: A Unified Platform for Reproducible and Reusable Recommender System Benchmarks0
Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao0
Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data0
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction0
PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving0
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1QNN-αAUC0.82Unverified
2FCNAUC0.82Unverified
3GDCNAUC0.82Unverified
4MemoNetAUC0.82Unverified
5TF4CTRAUC0.82Unverified
6FinalMLP + MMBAttnAUC0.81Unverified
7FinalMLPAUC0.81Unverified
8CETNAUC0.81Unverified
9STECAUC0.81Unverified
10DNN + MMBAttnAUC0.81Unverified
#ModelMetricClaimedVerifiedStatus
1OptInterAUC0.81Unverified
2OptInter-MAUC0.81Unverified
3CELSAUC0.8Unverified
4FCNAUC0.8Unverified
5CETNAUC0.8Unverified
6OptFSAUC0.8Unverified
7OptEmbedAUC0.79Unverified
8Sparse Deep FwFMAUC0.79Unverified
9FGCNN+IPNNAUC0.79Unverified
10Fi-GNNAUC0.78Unverified
#ModelMetricClaimedVerifiedStatus
1DeepFMAUC0.87Unverified
2FNNAUC0.87Unverified
3Wide & Deep (LR & DNN)AUC0.87Unverified
4PNN*AUC0.87Unverified
5IPNNAUC0.87Unverified
6Wide & Deep (FM & DNN)AUC0.87Unverified
7OPNNAUC0.87Unverified
8DeepMCPAUC0.77Unverified
#ModelMetricClaimedVerifiedStatus
1xDeepFMAUC0.84Unverified
2Wide & DeepAUC0.84Unverified
3DeepFMAUC0.84Unverified
4PNNAUC0.83Unverified
5RippleNetAUC0.68Unverified
6DKNAUC0.66Unverified
7DNNAUC0.03Unverified
#ModelMetricClaimedVerifiedStatus
1OPNNAUC0.82Unverified
2IPNNAUC0.79Unverified
3FCNAUC0.79Unverified
4OptInterAUC0.78Unverified
5OptInter-MAUC0.78Unverified
6PNN*AUC0.77Unverified
7FNNAUC0.76Unverified
#ModelMetricClaimedVerifiedStatus
1FCNAUC0.86Unverified
2DeepIMAUC0.85Unverified
3xDeepFMAUC0.85Unverified
4AutoInt+AUC0.85Unverified
5DeepFMAUC0.85Unverified
6DCNv2AUC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1STECAUC0.97Unverified
2KNIAUC0.94Unverified
3RippleNetAUC0.92Unverified
4MKRAUC0.92Unverified
5DCNv3AUC0.91Unverified
6AutoIntAUC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1github.com/guotong1988/movielens_datasetAUC0.79Unverified
2DIN + Dice ActivationAUC0.73Unverified
3DINAUC0.73Unverified
4DeepFMAUC0.73Unverified
5PNNAUC0.73Unverified
6Wide & DeepAUC0.73Unverified
#ModelMetricClaimedVerifiedStatus
1DIN + Dice ActivationAUC0.89Unverified
2DINAUC0.88Unverified
3DeepFMAUC0.87Unverified
4PNNAUC0.87Unverified
5Wide & DeepAUC0.86Unverified
#ModelMetricClaimedVerifiedStatus
1xDeepFMAUC0.86Unverified
2DeepFMAUC0.85Unverified
3PNNAUC0.84Unverified
4Wide & DeepAUC0.84Unverified
5DNNAUC0.83Unverified
#ModelMetricClaimedVerifiedStatus
1TF4CTRAUC0.99Unverified
2FinalMLPAUC0.99Unverified
3FinalMLP + MMBAttnAUC0.99Unverified
4DNN + MMBAttnAUC0.99Unverified
5AFN+AUC0.98Unverified
#ModelMetricClaimedVerifiedStatus
1FCNAUC0.81Unverified
2MemoNetAUC0.81Unverified
3OptEmbedAUC0.8Unverified
4OptFSAUC0.8Unverified
5AutoIntAUC0.79Unverified
#ModelMetricClaimedVerifiedStatus
1TF4CTRAUC0.97Unverified
2FinalMLPAUC0.97Unverified
3AFN+AUC0.95Unverified
#ModelMetricClaimedVerifiedStatus
1DSTN-IAUC0.84Unverified
2DeepMCPAUC0.79Unverified
#ModelMetricClaimedVerifiedStatus
1KGCN-sumAUC0.74Unverified
2RippleNetAUC0.73Unverified
#ModelMetricClaimedVerifiedStatus
1KGCN-concatAUC0.8Unverified
2MKRAUC0.69Unverified
#ModelMetricClaimedVerifiedStatus
1DIENAUC0.78Unverified
#ModelMetricClaimedVerifiedStatus
1NormDNNAUC0.74Unverified
#ModelMetricClaimedVerifiedStatus
1MKRAUC0.73Unverified
#ModelMetricClaimedVerifiedStatus
1FGCNN+IPNNAUC0.94Unverified