Fatigue-Aware Ad Creative Selection
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Abstract (arXiv)
In online display advertising, selecting the most effective ad creative (ad image) for each impression is a crucial task for DSPs (Demand-Side Platforms) to fulfill their goals (click-through rate, number of conversions, revenue, and brand improvement). As widely recognized in the marketing literature, the effect of ad creative changes with the number of repetitive ad exposures. In this study, we propose an efficient and easy-to-implement ad creative selection algorithm that explicitly considers user's psychological status when selecting ad creatives. The proposed system was deployed in a real-world production environment and tested against the baseline algorithms. The results show superiority of the proposed algorithm.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Aug 2019.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 1.
4 papers.
- 2022A Real-World Implementation of Unbiased Lift-based Bidding Systemcited by 2
- 2025Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoningcited by 2
- 2022Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networkscited by 1
- 2024State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewardscited by 0
- 2025Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoning18 Aug 2025
- 2024State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards18 Mar 2024
- 2022Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networks2 Apr 2022
- 2022A Real-World Implementation of Unbiased Lift-based Bidding System23 Feb 2022