Bias Mitigation for Large Language Models using Adversarial Learning. - Jasmina S. Ernst; Sascha Marton; Jannik Brinkmann; Eduardo Vellasques; Damien Foucard; Martin Kraemer; Marian Lambert (AEQUITAS@ECAI, 2023)

Evaluating Large Language Models and Prompt Variants on the Task of Detecting Cease and Desist Violations in German Online Product Descriptions. - Marian Lambert; Nico Döring; Thomas Schuster 001; Norbert Schmitz (DataMod, 2023)

Robustness Analysis of Machine Learning Models Using Domain-Specific Test Data Perturbation. - Marian Lambert; Thomas Schuster 001; Marcus Kessel; Colin Atkinson 001 (EPIA (1), 2023)

Using Large Language Models for the Enforcement of Consumer Rights in Germany. - Lukas Waidelich; Marian Lambert; Zina Al-Washash; Steffen Kroschwald; Thomas Schuster 001; Nico Döring (PLAIS, 2023)

Evaluating Privacy Patterns Within Collaborative Frameworks for AI Ecosystem Development. - Lukas Waidelich; Marian Lambert; Thomas Schuster 001 (PRO-VE (1), 2024)

Needle-in-the-Haystack Testing LLMs with a Complex Reasoning Task. - Thomas Schuster 001; Marian Lambert; Nico Döring; Julius Trögele (EANN (1), 2025)

Datenschutzkonformer LLM-Einsatz: Eine Open-Source-Referenzarchitektur. - Marian Lambert; Thomas Schuster 001; Nico Döring; Robin Krüger (CoRR, 2025)