Detecting Leaked Training Data in Large Language Models through Sampling-based Pseudo-Likelihood

A sampling-based pseudo-likelihood method (SaMIA) can effectively detect whether a given text is included in the training data of a large language model, without requiring access to the model's likelihood or loss.