# Auto-bidding and Auctions in Online Advertising: A Survey

arXiv: https://arxiv.org/abs/2408.07685 · HTML: https://mlsanity.com/paper/2408.07685/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Aug 2024.

## Built on by (most cited first, 26 of 26)

- [Generative Auto-Bidding with Value-Guided Explorations](https://mlsanity.com/paper/2504.14587/) (2025)
- [Joint Value Estimation and Bidding in Repeated First-Price Auctions](https://mlsanity.com/paper/2502.17292/) (2025)
- [Optimal Return-to-Go Guided Decision Transformer for Auto-Bidding in Advertisement](https://mlsanity.com/paper/2506.21956/) (2025)
- [A New Benchmark for Online Learning with Budget-Balancing Constraints](https://mlsanity.com/paper/2503.14796/) (2025)
- [Generative Large-Scale Pre-trained Models for Automated Ad Bidding Optimization](https://mlsanity.com/paper/2508.02002/) (2025)
- [Expert-Guided Diffusion Planner for Auto-Bidding](https://mlsanity.com/paper/2508.08687/) (2025)
- [From No-Regret to Strategically Robust Learning in Repeated Auctions](https://mlsanity.com/paper/2601.03853/) (2026)
- [Delayed Feedback Modeling for Post-Click Gross Merchandise Volume Prediction: Benchmark, Insights and Approaches](https://mlsanity.com/paper/2601.20307/) (2026)
- [Multi-agent Auto-Bidding with Latent Graph Diffusion Models](https://mlsanity.com/paper/2503.05805/) (2025)
- [Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms](https://mlsanity.com/paper/2510.19357/) (2025)
- [Learning to Bid with Unknown Private Values in Budget-Constrained First-Price Auctions](https://mlsanity.com/paper/2605.09448/) (2026)
- [Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?](https://mlsanity.com/paper/2605.31036/) (2026)
- [Learning to Coordinate Bidders in Non-Truthful Auctions](https://mlsanity.com/paper/2507.02801/) (2025)
- [Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash](https://mlsanity.com/paper/2509.07929/) (2025)
- [Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification](https://mlsanity.com/paper/2509.16324/) (2025)
- [Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards](https://mlsanity.com/paper/2510.20055/) (2025)
- [Q-Regularized Generative Auto-Bidding: From Suboptimal Trajectories to Optimal Policies](https://mlsanity.com/paper/2601.02754/) (2026)
- [Guiding the Recommender: Information-Aware Auto-Bidding for Content Promotion](https://mlsanity.com/paper/2601.20422/) (2026)
- [Is Online Linear Optimization Sufficient for Strategic Robustness?](https://mlsanity.com/paper/2602.12253/) (2026)
- [AHBid: An Adaptable Hierarchical Bidding Framework for Cross-Channel Advertising](https://mlsanity.com/paper/2602.22650/) (2026)
- [Uncertainty Quantification of Click and Conversion Estimates for the Autobidding](https://mlsanity.com/paper/2603.01825/) (2026)
- [NextAds: Towards Next-generation Personalized Video Advertising](https://mlsanity.com/paper/2603.02137/) (2026)
- [Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising](https://mlsanity.com/paper/2604.12799/) (2026)
- [Strategic Bidding in 6G Spectrum Auctions with Large Language Models](https://mlsanity.com/paper/2604.24156/) (2026)
- [Constrained Auto-Bidding via Generative Response Modeling](https://mlsanity.com/paper/2605.27811/) (2026)
- [Inference Auctions](https://mlsanity.com/paper/2609.40070/) (2026)

## Abstract (arXiv)

In this survey, we summarize recent developments in research fueled by the growing adoption of automated bidding strategies in online advertising. We explore the challenges and opportunities that have arisen as markets embrace this autobidding and cover a range of topics in this area, including bidding algorithms, equilibrium analysis and efficiency of common auction formats, and optimal auction design.