构建首个覆盖主流拍卖格式的自动出价基准，助力程序化广告算法研发。
BAT: Benchmark for Auto-bidding Task
- 设计涵盖两种主流拍卖格式的统一评测框架
- 提供预算分配与单次点击成本约束的标准化测试场景
- 适合研究程序化广告、实时竞价算法的开发者和学者
在线广告位拍卖中的出价策略优化是众多数字市场面临的关键挑战。制约实时自动出价算法研发、评估与改进的主要瓶颈在于缺乏全面的数据集和标准化基准。为此，我们提出一个涵盖两种最常见拍卖格式的拍卖基准。在新构建的数据集上，实现了一系列稳健基线，解决了实时竞价（RTB）中最具代表性的两大问题：预算配额均匀性和单次点击成本（CPC）约束优化。该基准为研究人员和实践者提供了友好且直观的框架，用于开发和优化创新的自动出价算法，推动程序化广告领域的发展。代码与资源可访问：https://github.com/avito-tech/bat-autobidding-benchmark, https://doi.org/10.5281/zenodo.14794182。
原文摘要 · Abstract (English)
The optimization of bidding strategies for online advertising slot auctions presents a critical challenge across numerous digital marketplaces. A significant obstacle to the development, evaluation, and refinement of real-time autobidding algorithms is the scarcity of comprehensive datasets and standardized benchmarks. To address this deficiency, we present an auction benchmark encompassing the two most prevalent auction formats. We implement a series of robust baselines on a novel dataset, addressing the most salient Real-Time Bidding (RTB) problem domains: budget pacing uniformity and Cost Per Click (CPC) constraint optimization. This benchmark provides a user-friendly and intuitive framework for researchers and practitioners to develop and refine innovative autobidding algorithms, thereby facilitating advancements in the field of programmatic advertising. The implementation and additional resources can be accessed at the following repository (https://github.com/avito-tech/bat-autobidding-benchmark, https://doi.org/10.5281/zenodo.14794182).
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