AI RESEARCH
Incentive-Aware Multi-Fidelity Optimization for Generative Advertising in Large Language Models
arXiv CS.LG
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ArXi:2604.06263v1 Announce Type: cross Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strategic behavior of advertisers and the high cost of stochastic generations. To address this, we propose the Incentive-Aware Multi-Fidelity Mechanism (IAMFM), a unified framework coupling Vickrey-Clarke-Groves (VCG) incentives with Multi-Fidelity Optimization to maximize expected social welfare.