Guijin Son

LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training

This work proposes LaRA, a layer-wise representation analysis framework for detecting contamination in RL post-trained LLMs and finds that contamination produces progressive geometric deviations across layers, including amplified perturbation sensitivity, stronger directional collapse, and enhanced local rigidity.