Code for Webis Papers accepted at The Web Conference 2024

This release links to the code for all papers at WWW`2024. Please follow the link in brackets to get to the respective repository.

Papers

• Schmidt et al. 2024; Detecting Generated Native Ads in Conversational Search [code]

Abstract

Conversational search engines such as YouChat and Microsoft Copilot use large language models (LLMs) to generate responses to queries. It is only a small step to also let the same technology insert ads within the generated responses - instead of separately placing ads next to a response. Inserted ads would be reminiscent of native advertising and product placement, both of which are very effective forms of subtle and manipulative advertising. Considering the high computational costs associated with LLMs, for which providers need to develop sustainable business models, users of conversational search engines may very well be confronted with generated native ads in the near future. In this paper, we thus take a first step to investigate whether LLMs can also be used as a countermeasure, i.e., to block generated native ads. We compile the Webis Generated Native Ads 2024 dataset of queries and generated responses with automatically inserted ads, and evaluate whether LLMs or fine-tuned sentence transformers can detect the ads. In our experiments, the investigated LLMs struggle with the task but sentence transformers achieve precision and recall values above 0.9.

Citation

@InProceedings{schmidt:2024,
  author =                   {Sebastian Schmidt and Ines Zelch and Janek Bevendorff and Benno Stein and Matthias Hagen and Martin Potthast},
  booktitle =                {WWW '24: Proceedings of the ACM Web Conference 2024},
  doi =                      {10.1145/3589335.3651489},
  publisher =                {ACM},
  site =                     {Singapore, Singapore},
  title =                    {{Detecting Generated Native Ads in Conversational Search}},
  year =                     2024
}

Initial release

Contributors Sebastian Schmidt, Ines Zelch, Janek Bevendorff, Benno Stein, Matthias Hagen, Martin Potthast