Knowing the Facts but Choosing the Shortcut: Understanding How Large Language Models Compare Entities
Conference of the European Chapter of the Association for Computational Linguistics (to appear) 2026
I am a principal investigator at the University of Hamburg, where I lead the DFG LUMO project. My research focuses on robust reasoning and interpretability to build trustworthy AI systems. More information can be found on the Research, Teaching, and CV pages.
Research Interests
Latest News
- Mar 2026 The LUMO project has now an official website with detailed information about the project, the team, and the research. Check it out!
- Jan 2026 Our paper Knowing the Facts but Choosing the Shortcut: Understanding How Large Language Models Compare Entities has been accepted to EACL 2026.
- Oct 2025 Tutorial on Explaining Vision and Language Models: A Concept-Based Approach at ECAI 2025 (with Dr. Gesina Schwalbe).
Recent Publications
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Mental Modelling of Reinforcement Learning Agents by Language Models
Transactions on Machine Learning Research 2025
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Towards Ethical Multi-Agent Systems of Large Language Models: A Mechanistic Interpretability Perspective
Presented at LLM-based Multi-Agent Systems: Towards Responsible, Reliable, and Scalable Agentic Systems (LaMAS 2026) 2025
Recent Blog Posts
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Deep Learning Courses and Books for Beginners
A curated list of deep learning resources for CS students who want to understand recent research papers.
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Common LaTeX Mistakes by Newbies
A list of common LaTeX mistakes that beginners often make, with examples of correct usage.