Gengda Zhao

Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection

CalibDCD is proposed, a broadly applicable calibration framework for feature-based DCD methods, comprising Multi-View Shift Detection, which identifies recurring feature shifts associated with post-training, and Bounded Feature Correction, which selectively mitigates their influence on membership prediction.