Training LLM Deception Detectors on One Lie Type Fails on Others—Taxonomy Needed
Researchers examined how probe depth, expressivity, and feature sparsity affect LLM deception detection. They found that detectors trained on a single lie type (e.g., fabrication) perform poorly on other types like omission or exaggeration, and that data diversity and lie taxonomy dominate performance more than model complexity.