3 papers
cs.HC2026
Human-Centred LLM Privacy Audits: Findings and Frictions
Dimitri Staufer, Kirsten Morehouse, David Hartmann +1
Large language models (LLMs) learn statistical associations from massive training corpora and user interactions, and deployed systems can surface or infer information about individ…
cs.LG2026
Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs
David Hartmann, Lena Pohlmann, Lelia Hanslik +3
Large Language Models (LLMs) exhibit systematic biases across demographic groups. Auditing is proposed as an accountability tool for black-box LLM applications, but suffers from re…
cs.SI2024
A Systematic Review of Echo Chamber Research: Comparative Analysis of Conceptualizations, Operationalizations, and Varying Outcomes
David Hartmann, Sonja Mei Wang, Lena Pohlmann +1
This systematic review synthesizes research on echo chambers and filter bubbles to explore the reasons behind dissent regarding their existence, antecedents, and effects. It provid…