mlsanityData to 7 Oct 2026

Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed

arXiv 2401.01656 ↗First posted 3 Jan 2024cs.GT cs.AIcited by 6

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Abstract (arXiv)

E-commerce platforms usually present an ordered list, mixed with several organic items and an advertisement, in response to each user's page view request. This list, the outcome of ad auction and allocation processes, directly impacts the platform's ad revenue and gross merchandise volume (GMV). Specifically, the ad auction determines which ad is displayed and the corresponding payment, while the ad allocation decides the display positions of the advertisement and organic items. The prevalent methods of segregating the ad auction and allocation into two distinct stages face two problems: 1) Ad auction does not consider externalities, such as the influence of actual display position and context on ad Click-Through Rate (CTR); 2) The ad allocation, which utilizes the auction-winning ad's payment to determine the display position dynamically, fails to maintain incentive compatibility (IC) for the advertisement. For instance, in the auction stage employing the traditional Generalized Second Price (GSP) , even if the winning ad increases its bid, its payment remains unchanged. This implies that the advertisement cannot secure a better position and thus loses the opportunity to achieve higher utility in the subsequent ad allocation stage. Previous research often focused on one of the two stages, neglecting the two-stage problem, which may result in suboptimal outcomes...

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 35 references that are in the map. First posted on arXiv 3 Jan 2024.

Builds on

15 of 35 references.

References · 15

  1. 2017Attention Is All You Needcited by 59,932
  2. 2017Deep Interest Network for Click-Through Rate Predictioncited by 541
  3. 2019DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systemscited by 44
  4. 2021Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertisingcited by 31
  5. 2021Cross DQN: Cross Deep Q Network for Ads Allocation in Feedcited by 18
  6. 2021Deep Position-wise Interaction Network for CTR Predictioncited by 8
  7. 2022Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocationcited by 8
  8. 2022Hierarchically Constrained Adaptive Ad Exposure in Feedscited by 6
  9. 2022Hybrid Transfer in Deep Reinforcement Learning for Ads Allocationcited by 5
  10. 2022NMA: Neural Multi-slot Auctions with Externalities for Online Advertisingcited by 4
  11. 2022Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Taskscited by 3
  12. 2015Ad auctions and cascade model: GSP inefficiency and algorithmscited by 2
3 more
  1. 2023Multi-channel Integrated Recommendation with Exposure Constraintscited by 2
  2. 2020Optimally Integrating Ad Auction into E-Commerce Platformscited by 1
  3. 2023MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feedcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 5.

6 papers.

  1. 2026Distributed General-Purpose Agent Networks: Architecture, Key Mechanisms, and Prototypescited by 3
  2. 2024Automated Deterministic Auction Design with Objective Decompositioncited by 2
  3. 2026LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbotscited by 2
  4. 2026Open Problems in Differentiable Social Choice: Learning Mechanisms, Decisions, and Alignmentcited by 0
  5. 2026Enhancing Affine Maximizer Auctions with Correlation-Aware Paymentcited by 0
  6. 2026Uniboost: Global Coordination with Value Alignment for Fair and Efficient Traffic Allocationcited by 0