# Incentive Mechanism Design for ROI-constrained Auto-bidding

arXiv: https://arxiv.org/abs/2012.02652 · HTML: https://mlsanity.com/paper/2012.02652/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2020.

## Built on by (most cited first, 2 of 2)

- [A Unifying Framework for Online Optimization with Long-Term Constraints](https://mlsanity.com/paper/2209.07454/) (2022)
- [BAT: Benchmark for Auto-bidding Task](https://mlsanity.com/paper/2505.08485/) (2025)

## Abstract (arXiv)

Auto-bidding plays an important role in online advertising and has become a crucial tool for advertisers and advertising platforms to meet their performance objectives and optimize the efficiency of ad delivery. Advertisers employing auto-bidding only need to express high-level goals and constraints, and leave the bid optimization problem to the advertising platforms. As auto-bidding has obviously changed the bidding language and the way advertisers participate in the ad auction, fundamental investigation into mechanism design for auto-bidding environment should be made to study the interaction of auto-bidding with advertisers. In this paper, we formulate the general problem of incentive mechanism design for ROI-constrained auto-bidding, and carry out analysis of strategy-proof requirements for the revenue-maximizing and profit-maximizing advertisers. In addition, we provide a mechanism framework and a practical solution to guarantee the incentive property for different types of advertisers.