arXiv (All)
open access
LLM-OSDA: An Optimal-Stopping Dynamic Auction for Native Advertising in Multi-Turn LLM Conversations
68t07artificial-intelligencecomputation-and-languagecomputer-science-and-game-theoryi-2-6i-2-7machine-learning
LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within an evolving conversation. Existing LLM ad-auction mechanisms primarily operate within a single response, settling the winner but not the timing. The
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Beyond Independent Values: Optimal Auctions with Correlated Valuations for LLM-Native Advertising#1325542
- Degree-Parameterized Analysis of Sampling-Based Online Matching#1083917
- Phonology-Aware Speaker Extraction Frontend for Audio LLMs#1297852
- Towards Multi-Model LLM Schedulers: Empirical Insights into Offloading and Preemption#798900
- Towards Multi-Model LLM Schedulers: Empirical Insights into Offloading and Preemption#797486
Record · ID 1342568
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive