English(EN) Monetizing Intelligence: Advertising and Subscription Design on LLM Platforms

学术论文分析通过广告和订阅对LLM进行变现

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

一篇新的学术论文探讨了将广告和订阅模式整合到大型语言模型（LLM）平台中的经济影响。研究表明，广告可以补贴那些否则不会付费使用的用户的服务质量，可能导致不同服务层级用户效用的两极分化。研究还指出，最优的广告上限可以最大化消费者剩余，而计算效率的提高可能通过提高服务质量来悖论式地增加广告收入。 AI

影响为理解AI平台的商业模式提供了经济学框架。

排序理由学术论文发表在arXiv上 [lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 15 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 学术论文发表在arXiv上 [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

arXiv cs.AI TIER_1 English(EN) · Yuhang Ji, Fasheng Xu, Tianjun Feng · 2026-10-26 04:00

将智能变现：LLM平台上的广告与订阅设计

arXiv:2610.32945v1 Announce Type: cross Abstract: Large language model (LLM) platforms introducing advertising must decide how much capability ad revenue should fund and what consumers should pay to avoid ads. We study a monopolistic platform that jointly chooses costly response …