Online Advertisements with LLMs: Opportunities and Challenges
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Acceso en línea: | |
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| _version_ | 1866910593947009024 |
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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 |