mlsanityData to 14 Oct 2026

Deep CTR Prediction in Display Advertising

arXiv 1609.06018 ↗First posted 20 Sep 2016cs.CV cs.MMcited by 31

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Abstract (arXiv)

Click through rate (CTR) prediction of image ads is the core task of online display advertising systems, and logistic regression (LR) has been frequently applied as the prediction model. However, LR model lacks the ability of extracting complex and intrinsic nonlinear features from handcrafted high-dimensional image features, which limits its effectiveness. To solve this issue, in this paper, we introduce a novel deep neural network (DNN) based model that directly predicts the CTR of an image ad based on raw image pixels and other basic features in one step. The DNN model employs convolution layers to automatically extract representative visual features from images, and nonlinear CTR features are then learned from visual features and other contextual features by using fully-connected layers. Empirical evaluations on a real world dataset with over 50 million records demonstrate the effectiveness and efficiency of this method.

Key facts. Cited by 31 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Sep 2016.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 6; 2024: 5; 2025: 5; 2026: 3.

31 papers.

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  1. 2022Click-Through Rate Prediction in Online Advertising: A Literature Reviewcited by 31
  2. 2024Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insightscited by 23
  3. 2021User Response Prediction in Online Advertisingcited by 15
  4. 2021A Hybrid Bandit Model with Visual Priors for Creative Ranking in Display Advertisingcited by 15
  5. 2021HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environmentscited by 15
  6. 2023Large Language Models are Not Stable Recommender Systemscited by 13
  7. 2021Efficient Optimal Selection for Composited Advertising Creatives with Tree Structurecited by 5
  8. 2021Online Advertising Revenue Forecasting: An Interpretable Deep Learning Approachcited by 5
  9. 2021Nonuniform Negative Sampling and Log Odds Correction with Rare Events Datacited by 4
  10. 2024Confidence-Aware Multi-Field Model Calibrationcited by 4
  11. 2024Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendationcited by 4
  12. 2025Field Matters: A Lightweight LLM-enhanced Method for CTR Predictioncited by 4
19 more
  1. 2022Hybrid CNN Based Attention with Category Prior for User Image Behavior Modelingcited by 2
  2. 2024Improved Online Learning Algorithms for CTR Prediction in Ad Auctionscited by 2
  3. 2025Macro Graph of Experts for Billion-Scale Multi-Task Recommendationcited by 2
  4. 2022Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networkscited by 1
  5. 2022DM2S2: Deep Multi-Modal Sequence Sets with Hierarchical Modality Attentioncited by 1
  6. 2023Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctionscited by 1
  7. 2023Cross-Element Combinatorial Selection for Multi-Element Creative in Display Advertisingcited by 1
  8. 2024GACE: Learning Graph-Based Cross-Page Ads Embedding For Click-Through Rate Predictioncited by 1
  9. 2025Generative Modeling with Multi-Instance Reward Learning for E-commerce Creative Optimizationcited by 1
  10. 2021M2FN: Multi-step Modality Fusion for Advertisement Image Assessmentcited by 0
  11. 2022AI-Driven Contextual Advertising: A Technology Report and Implication Analysiscited by 0
  12. 2023Improving Prediction Performance and Model Interpretability through Attention Mechanisms from Basic and Applied Research Perspectivescited by 0
  13. 2023Beyond Rankings: Exploring the Impact of SERP Features on Organic Click-through Ratescited by 0
  14. 2023AdSEE: Investigating the Impact of Image Style Editing on Advertisement Attractivenesscited by 0
  15. 2025PRECTR: A Synergistic Framework for Integrating Personalized Search Relevance Matching and CTR Predictioncited by 0
  16. 2025Toward a benchmark for CTR prediction in online advertising: datasets, evaluation protocols and perspectivescited by 0
  17. 2026DAIAN: Deep Adaptive Intent-Aware Network for CTR Prediction in Trigger-Induced Recommendationcited by 0
  18. 2026Decoding the Hook: A Multimodal LLM Framework for Analyzing the Hooking Period of Video Adscited by 0
  19. 2026Generative Long-term User Interest Modeling for Click-Through Rate Predictioncited by 0