Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.14473

Diffusion-Based Auctions for Multi-Winner Banner Ads

Lilian Sun·Henry Huang·Fucheng Warren Zhu·Giannis Daras·Constantinos Daskalakis
View original source ↗Read source document ↗Export metadata ↓

Abstract

We propose a new framework for banner ad auctions, leveraging diffusion models to allow for multiple bidders to co-win a single banner ad opportunity, and in particular influence the ad shown on the banner depending on the strength of their bids, enabling a far richer outcome space compared to standard banner ad auctions, where there is a single winner who shows their ad. In our framework, the outcomes are images (what ad to show) and each bidder expresses their preferences over outcomes by declaring their value per unit of alignment between the image chosen by the mechanism and a textual description of their desired image. Our proposed mechanism combines the advertisers' bids and textual descriptions into a score that drives the reverse process of a diffusion model. This is used to sample a set of candidate images from which the welfare maximizing one is eventually chosen. Extensive experimentation evaluates our proposed mechanism around the following axes: (1) efficiency improvements of our allocation rule relative to the single-winner allocation rule; (2) monotonicity of our allocation rule; and (3) approximate incentive compatibility when combining our allocation rule with Myerson lemma-based or Clarke rule-based payments. Improvements along all these axes are shown with the number of Monte Carlo samples. Meanwhile, these benefits are attained while preserving the image quality.

Explore related subjects

cs.GTcs.AIcs.LG

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lilian Sun, Henry Huang, Fucheng Warren Zhu, Giannis Daras, Constantinos Daskalakis. 2026-10-10. Diffusion-Based Auctions for Multi-Winner Banner Ads. https://arxiv.org/abs/2610.14473

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Matching Markets: Equilibrium Computation, Indivisible Goods, and Positional Externalities

Matching markets provide a mathematical framework for allocating scarce resources among strategic agents with heterogeneous preferences. While matching without money relies on ordinal stability and Pareto efficiency, Fisher and Arrow--Debreu markets mediate allocation through budgets and market-clearing prices. In this paper, we study the convex-analytic foundations, computational complexity, and external-utility extensions of Fisher matching markets. First, we formulate fractional resource allocation and linear Fisher markets via Fenchel conjugate duality and the Karush--Kuhn--Tucker (KKT) conditions of the Eisenberg--Gale convex program, showing how budget-weighted Nash social welfare characterizes competitive equilibria across linear and homothetic utility families. Second, we review topological existence via Sperner's lemma alongside polynomial-time combinatorial algorithms for divisible markets, including the Devanur--Papadimitriou--Saberi--Vazirani (DPSV) primal-dual max-flow algorithm and Orlin's strongly polynomial scaling algorithm. Third, we contrast the tractability of divisible markets with the $\mathsf{NP}$-hardness and $\mathsf{PPAD}$-completeness of indivisible Fisher markets and Competitive Equilibrium from Equal Incomes (CEEI), comparing $\varepsilon$-approximate equilibria, CEEI-FRAC, and Budish's Approximate CEEI mechanism. Finally, we analyze Fisher markets with positional (snob-effect) externalities, where buyer $i$'s utility for good $j$ scales with her relative share $(x_{ij}/\sum_{k} x_{kj})^{α_i}$ for $α_i > 0$. We prove that positional utility summands are convex on the nonnegative orthant, so utilitarian social welfare is maximized at exclusive corner allocations, whereas decentralized price-taking admits a unique budget-proportional equilibrium in single-good snob markets with a Price of Anarchy of $n^α$ among $n$ symmetric buyers.

cs.GT↗
arXiv2026

Achieving Pareto Optimality in Games via Single-bit Feedback

Efficient coordination in multi-agent systems often incurs high communication overhead or slow convergence rates, making scalable welfare optimization difficult. We propose Single-Bit Coordination Dynamics for Pareto-Efficient Outcomes (SBC-PE), a decentralized learning algorithm requiring only a single-bit satisfaction signal per agent each round. Despite this extreme efficiency, SBC-PE guarantees convergence to the exact optimal solution in arbitrary finite games. We establish explicit regret bounds, showing expected regret grows only logarithmically with the horizon, i.e., O(log T). Compared with prior payoff-based or bandit-style rules, SBC-PE uniquely combines minimal signaling, general applicability, and finite-time guarantees. These results show scalable welfare optimization is achievable under minimal communication constraints.

cs.GT↗
arXiv2026

Continuation-Adjusted Full-Support Indifference in a Feedback Stackelberg Attacker--Defender Attrition Game

Successful attacks that remove assets break two familiar static regularities: coverage need not deter attack, and the defender need not push coverage until its budget or an individual target saturates. We analyse a finite-horizon attacker--defender attrition game under a stagewise feedback-recommitment strong Stackelberg equilibrium. Our central result is a continuation adjustment that converts each state--period node into a static security game with shifted payoffs. At feasible full-support nodes, coverage remains indexed by one scalar attacker value, so backward induction uses scalar interval and endpoint calculations; boundary-support nodes require conditional linear programmes. Continuation losses can reverse an attacker's coverage swing, making a covered asset more attractive because it survives for later attacks. A three-asset, two-period instance is solved globally for every discount factor. It exhibits an exact singular threshold at which the optimal set expands, the selected policy jumps, and the defender abandons a previously protected asset and leaves budget unused with no target saturated, although both players' values remain continuous.

cs.GT↗