Papers by Yuanhong Huang

1 papers
Robust Membership Inference for Large Language Models under Adversarial Generative Corruption (2026.acl-long)

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Challenge: Membership inference attacks are a promising tool for auditing training data of LLMs . existing methods rely on the assumption that LLM's assign higher confidence scores to training samples than to non-training ones.
Approach: They propose a membership inference framework that can be robust against adversarial MIAs.
Outcome: The proposed framework can be robust against adversarial MIA methods and AIGT detectors while maintaining the performance of baselines.

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