6 citations · 11 across the 5 of their papers we have counts for
5 papers
Formalized Information Needs Improve Large-Language-Model Relevance Judgments
Jüri Keller, Maik Fröbe, Björn Engelmann +4
Cranfield-style retrieval evaluations with too few or too many relevant documents or with low inter-assessor agreement on relevance can reduce the reliability of observations. In e…
REANIMATOR: Reanimate Retrieval Test Collections with Extracted and Synthetic Resources
Björn Engelmann, Fabian Haak, Philipp Schaer +3
Retrieval test collections are essential for evaluating information retrieval systems, yet they often lack generalizability across tasks. To overcome this limitation, we introduce…
Investigating Bias in Political Search Query Suggestions by Relative Comparison with LLMs
Fabian Haak, Björn Engelmann, Christin Katharina Kreutz +1
Search query suggestions affect users' interactions with search engines, which then influences the information they encounter. Thus, bias in search query suggestions can lead to ex…
Context-Driven Interactive Query Simulations Based on Generative Large Language Models
Björn Engelmann, Timo Breuer, Jana Isabelle Friese +2
Simulating user interactions enables a more user-oriented evaluation of information retrieval (IR) systems. While user simulations are cost-efficient and reproducible, many approac…
Simulating Users in Interactive Web Table Retrieval
Björn Engelmann, Timo Breuer, Philipp Schaer
Considering the multimodal signals of search items is beneficial for retrieval effectiveness. Especially in web table retrieval (WTR) experiments, accounting for multimodal propert…