activity
20182024
most citedPerspectives on Large Language Models for Relevance Judgment

170 citations · 388 across the 16 of their papers we have counts for

collaborators

18 papers

cs.IR2024★ 10 cited

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…

cs.IR2023★ 44 cited

Evaluating Generative Ad Hoc Information Retrieval

Lukas Gienapp, Harrisen Scells, Niklas Deckers +9

Recent advances in large language models have enabled the development of viable generative retrieval systems. Instead of a traditional document ranking, generative retrieval system…

cs.IR2023★ 3 cited

Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search

Ines Zelch, Matthias Hagen, Martin Potthast

How will generative AI pay for itself? Unless charging users for access, selling advertising is the only alternative. Especially in the multi-billion dollar web search market with…

cs.IR2023★ 54 cited

The Information Retrieval Experiment Platform

Maik Fröbe, Jan Heinrich Reimer, Sean MacAvaney +6

We integrate ir_datasets, ir_measures, and PyTerrier with TIRA in the Information Retrieval Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and ev…

cs.IR2023★ 170 cited

Perspectives on Large Language Models for Relevance Judgment

Guglielmo Faggioli, Laura Dietz, Charles Clarke +8

When asked, large language models (LLMs) like ChatGPT claim that they can assist with relevance judgments but it is not clear whether automated judgments can reliably be used in ev…

cs.IR2023★ 11 cited

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…