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cs.LG2026
WildTrace: Evaluating Training Data Detection in Realistic Large-Scale LLM Post-Training
Hengxiang Zhang, Junxian Liu, Hongxin Wei
Although post-training significantly enhances model performance, the use of massive undisclosed data raises concerns about benchmark contamination and copyright infringement. This…
cs.LG2024
Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning
Hengxiang Zhang, Qiang Hu, Hongxin Wei
Over-parameterized models are typically vulnerable to membership inference attacks, which aim to determine whether a specific sample is included in the training of a given model. P…