Huili Wang

Robust Membership Inference for Large Language Models under Adversarial Generative Corruption

A robust membership inference framework for reliably identifying training data that adopts a mixture-of-experts formulation to jointly model interactions across complementary features derived from multiple MIA methods and AIGT detectors, which can remain robust against ad-versarially generated samples.