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Hauptverfasser: Feizi, Soheil, Hajiaghayi, MohammadTaghi, Rezaei, Keivan, Shin, Suho
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2311.07601
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author Feizi, Soheil
Hajiaghayi, MohammadTaghi
Rezaei, Keivan
Shin, Suho
author_facet Feizi, Soheil
Hajiaghayi, MohammadTaghi
Rezaei, Keivan
Shin, Suho
contents This paper explores the potential for leveraging Large Language Models (LLM) in the realm of online advertising systems. We introduce a general framework for LLM advertisement, consisting of modification, bidding, prediction, and auction modules. Different design considerations for each module are presented. These design choices are evaluated and discussed based on essential desiderata required to maintain a sustainable system. Further fundamental questions regarding practicality, efficiency, and implementation challenges are raised for future research. Finally, we exposit how recent approaches on mechanism design for LLM can be framed in our unified perspective.
format Preprint
id arxiv_https___arxiv_org_abs_2311_07601
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Online Advertisements with LLMs: Opportunities and Challenges
Feizi, Soheil
Hajiaghayi, MohammadTaghi
Rezaei, Keivan
Shin, Suho
Computers and Society
Artificial Intelligence
This paper explores the potential for leveraging Large Language Models (LLM) in the realm of online advertising systems. We introduce a general framework for LLM advertisement, consisting of modification, bidding, prediction, and auction modules. Different design considerations for each module are presented. These design choices are evaluated and discussed based on essential desiderata required to maintain a sustainable system. Further fundamental questions regarding practicality, efficiency, and implementation challenges are raised for future research. Finally, we exposit how recent approaches on mechanism design for LLM can be framed in our unified perspective.
title Online Advertisements with LLMs: Opportunities and Challenges
topic Computers and Society
Artificial Intelligence
url https://arxiv.org/abs/2311.07601