6 citations · 15 across the 9 of their papers we have counts for
9 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…
Dynamics in Search Engine Query Suggestions for European Politicians
Franziska Pradel, Fabian Haak, Sven-Oliver Proksch +1
Search engines are commonly used for online political information seeking. Yet, it remains unclear how search query suggestions for political searches that reflect the latent inter…
Pairwise Comparison for Bias Identification and Quantification
Fabian Haak, Philipp Schaer
Linguistic bias in online news and social media is widespread but difficult to measure. Yet, its identification and quantification remain difficult due to subjectivity, context dep…
Sim4IA-Bench: A User Simulation Benchmark Suite for Next Query and Utterance Prediction
Andreas Konstantin Kruff, Christin Katharina Kreutz, Timo Breuer +2
Validating user simulation is a difficult task due to the lack of established measures and benchmarks, which makes it challenging to assess whether a simulator accurately reflects…
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…
Building an Explainable Graph-based Biomedical Paper Recommendation System (Technical Report)
Hermann Kroll, Christin K. Kreutz, Bill Matthias Thang +2
Digital libraries provide different access paths, allowing users to explore their collections. For instance, paper recommendation suggests literature similar to some selected paper…
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…