A quality-preserving auction framework for LLM advertising uses RAG-based endogenous reserves and KL-regularized or screened VCG mechanisms to achieve DSIC, IR, higher revenue, and better semantic fidelity than baselines.
Ad auctions for llms via retrieval augmented generation.Advances in Neural Information Processing Systems, 37:18445–18480
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LERA is a retrieve-then-generate auction system that refines ad candidate ranking with LLM logits and applies a threshold-aware critical-value payment rule to maintain truthfulness in chatbot ad insertion.
citing papers explorer
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Mechanism Design for Quality-Preserving LLM Advertising
A quality-preserving auction framework for LLM advertising uses RAG-based endogenous reserves and KL-regularized or screened VCG mechanisms to achieve DSIC, IR, higher revenue, and better semantic fidelity than baselines.
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LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots
LERA is a retrieve-then-generate auction system that refines ad candidate ranking with LLM logits and applies a threshold-aware critical-value payment rule to maintain truthfulness in chatbot ad insertion.