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
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
Rethinking Position Bias Modeling with Knowledge Distillation for CTR Prediction0
Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction0
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation0
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation0
ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training0
Single-shot Embedding Dimension Search in Recommender System0
SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction0
Soft Retargeting Network for Click Through Rate Prediction0
Sparse Tensor Additive Regression0
Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location-based Services0
Star+: A New Multi-Domain Model for CTR Prediction0
STEC: See-Through Transformer-based Encoder for CTR Prediction0
Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data0
TBIN: Modeling Long Textual Behavior Data for CTR Prediction0
Temporal Importance Factor for Loss Functions for CTR Prediction0
TFNet: Multi-Semantic Feature Interaction for CTR Prediction0
The Effects of Data Split Strategies on the Offline Experiments for CTR Prediction0
Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction0
Towards An Efficient LLM Training Paradigm for CTR Prediction0
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction0
Towards Personality-Aware Recommendation0
Towards Practical Second Order Optimization for Deep Learning0
Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions0
Towards Unifying Feature Interaction Models for Click-Through Rate Prediction0
Training with Multi-Layer Embeddings for Model Reduction0
TSI: an Ad Text Strength Indicator using Text-to-CTR and Semantic-Ad-Similarity0
TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou0
Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models0
U-rank: Utility-oriented Learning to Rank with Implicit Feedback0
Using Neural Networks for Click Prediction of Sponsored Search0
Visual Encoding and Debiasing for CTR Prediction0
Visualizing and Understanding Deep Neural Networks in CTR Prediction0
v-TCM: Vertical-aware Transformer Click Model for Web Search0
Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions0
0/1 Deep Neural Networks via Block Coordinate Descent0
You Must Have Clicked on this Ad by Mistake! Data-Driven Identification of Accidental Clicks on Mobile Ads with Applications to Advertiser Cost Discounting and Click-Through Rate Prediction0
HMDN: Hierarchical Multi-Distribution Network for Click-Through Rate Prediction0
A Bag of Tricks for Scaling CPU-based Deep FFMs to more than 300m Predictions per Second0
A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features0
A Collaborative Ensemble Framework for CTR Prediction0
A Collaborative Transfer Learning Framework for Cross-domain Recommendation0
AdaEnsemble: Learning Adaptively Sparse Structured Ensemble Network for Click-Through Rate Prediction0
AdaptDHM: Adaptive Distribution Hierarchical Model for Multi-Domain CTR Prediction0
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction0
AdaSparse: Learning Adaptively Sparse Structures for Multi-Domain Click-Through Rate Prediction0
Addressing Cold-start Problem in Click-Through Rate Prediction via Supervised Diffusion 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