Game-Theoretic Model Finds Real-World GenAI Search Citation Mechanisms Are Unstable for Publishers

arXiv 2607.25514·medium signalXBlueskyLinkedInCopy link

A paper posted 2026-07-28 (arXiv 2607.25514) builds a game-theoretic model of the emerging generative-search ecosystem, where publishers compete for attribution-based exposure inside generated answers rather than for position in a ranked list — a fundamentally different incentive than classic SEO content modification. Studying better-response learning dynamics and using potential-games machinery, the authors associate convergence to equilibrium with ecosystem stability, and show that mechanisms representing real-world modern systems are unstable, while characterizing one content-selection mechanism that does induce stability. Extensive simulations support the theory and surface a trade-off platform designers cannot dodge: stable mechanisms do not necessarily maximize welfare, and publisher welfare trades against distinct sources of user welfare.