Nov 2026· Proceedings of the 35th ACM International Conference on Information and Knowledge Management· 0 citations· 12 references
Auction Theory and Applications
Abstract
Automated bidding in Demand-Side Platforms (DSPs) aims to maximize overall value while satisfying diverse advertiser constraints. However, scaling to practical deployments reveals two structural challenges: cross-granularity constraint conflicts between advertiser-level decisions and business-line KPIs, and bid homogenization under first-price auctions that erodes platform surplus. Existing single-advertiser AI Generative Bidding (AIGB) methods fundamentally fail to address these platform-wide issues. We propose PGBid (Platform-Wide Generative Auto-Bidding), a macro-micro decoupled framework. At the macro level, a Strategist uses convex optimization to decompose global constraints into per-advertiser targets. At the micro level, a Tactician combines a conditional diffusion model with a distribution-aware inverse dynamics model to translate these targets into bidding distributions for fine-grained bid shading. Extensive offline experiments and large-scale online A/B testing demonstrate that PGBid significantly outperforms state-of-the-art baselines. Moreover, PGBid has been fully deployed on our DSP platform, reliably processing billions of bid requests daily.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
Objective There is dearth of information on the timeliness of antenatal care (ANC) uptake. This study aimed to determine the timely ANC uptake by a medically trained provider (MTP) as per the World Health Organization (WHO) recommendations and the country guideline. Methods Cross-sectional survey was done with 2,731 wo...
B. Sarker, Musfikur Rahman, T. Rahman et al.· PLoS ONE· 89 citations· ⚡7
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
