Papers with layer-wise representation dynamics
Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis (2026.eacl-long)
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| Challenge: | Membership inference attacks (MIAs) reveal whether specific data was used to train machine learning models, serving as important tools for privacy auditing and compliance assessment. |
| Approach: | They propose to examine LLMs’ internal representations rather than just their outputs to gain additional insights into potential membership inference signals. |
| Outcome: | The proposed framework yields strong membership detection across several model families achieving average AUC scores of 0.85 on popular MIA benchmarks. |