11 citations · 21 across the 4 of their papers we have counts for
4 papers
Detecting RAG Advertisements Across Advertising Styles
Sebastian Heineking, Wilhelm Pertsch, Ines Zelch +4
Large language models (LLMs) enable a new form of advertising for retrieval-augmented generation (RAG) systems in which organic responses are blended with contextually relevant ads…
Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions
Sebastian Heineking, Jonas Probst, Daniel Steinbach +2
Evaluating the output of generative large language models (LLMs) is challenging and difficult to scale. Many evaluations of LLMs focus on tasks such as single-choice question-answe…
Detecting Generated Native Ads in Conversational Search
Sebastian Schmidt, Ines Zelch, Janek Bevendorff +3
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…
The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives
Jan Heinrich Reimer, Sebastian Schmidt, Maik Fröbe +5
The Archive Query Log (AQL) is a previously unused, comprehensive query log collected at the Internet Archive over the last 25 years. Its first version includes 356 million queries…