Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search
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%0 Generic
%1 zelch2023commercializedgenerativeaicritical
%A Zelch, Ines
%A Hagen, Matthias
%A Potthast, Martin
%D 2023
%K topic_language imported
%T Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search
%U https://arxiv.org/abs/2310.04892
@misc{zelch2023commercializedgenerativeaicritical,
added-at = {2024-11-19T15:34:37.000+0100},
archiveprefix = {arXiv},
author = {Zelch, Ines and Hagen, Matthias and Potthast, Martin},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/209c40f3a6446371da8403f0f2aa0b107/scadsfct},
eprint = {2310.04892},
interhash = {5d8c8d86a738ce1a29300ec8c4aca3b9},
intrahash = {09c40f3a6446371da8403f0f2aa0b107},
keywords = {topic_language imported},
primaryclass = {cs.IR},
timestamp = {2024-11-28T17:41:15.000+0100},
title = {Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search},
url = {https://arxiv.org/abs/2310.04892},
year = 2023
}