George Kesidis — Papers on Cortexa

arxivcs.CRcs.AIcs.LG2026-06-30

CSO-LLM: Class Subspace Orthogonalization for Post-Training Backdoor Detection and Trigger Inversion in LLMs

Zhengxing Li, David J. Miller, Guangmingmei Yang, George Kesidis

While post-training backdoor detection and trigger inversion schemes have been developed for AIs used e.g. for images, there is a paucity of such methods for LLMs. First, the LLM input space is discrete, with up to 150,000^k k-tuples to consider with k the token-length of a putat…

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arxivcs.LG2026-06-27

A Novel Latent-Class Attack and its Detection by Class Subspace Orthogonalization

Guangmingmei Yang, David J. Miller, George Kesidis

Deep learning, which in general relies on voluminous amounts of training data, is vulnerable to data poisoning attacks, including error-generic attacks and backdoors (Trojans). In this work, we propose a new data poisoning attack we dub a latent class attack. Here, all poisoned e…

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