Probing Ethical Framework Representations in Large Language Models: Structure, Entanglement, and Methodological Challenges

Researchers analyzed how large language models (4B-72B parameters) internally represent different ethical frameworks, finding that models create distinct ethical subspaces but with asymmetric transfer patterns between frameworks. The study reveals structural insights into AI ethics processing while highlighting methodological limitations in probing techniques.