Hugging Face Trending Papers June 8, 2026

Pretrained, Frozen, Still Leaking: Auditing Cross-Encoder Attribute Transfer in EEG Foundation Models

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EEG foundation-model releases are usually audited one endpoint at a time: raw-reconstruction, membership inference, identity linkage, or DP-SGD on the downstream head. We audit the same released embeddings under all four endpoints jointly, on BIOT, LaBraM, and EEGPT, and show that each single-endpoint audit clears releases that still leak spectral attributes.

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arXiv AI

Jun 9

Pretrained, Frozen, Still Leaking: Auditing Cross-Encoder Attribute Transfer in EEG Foundation Models

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arXiv Machine Learning

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arXiv AI

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arXiv AI

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Related stories

Pretrained, Frozen, Still Leaking: Auditing Cross-Encoder Attribute Transfer in EEG Foundation Models

Brain-Prompt Injection: A Route-Safety Audit for BCI-LLM Agents

What EEG Foundation Models Encode: Dataset Identity and a Negative-Control Suite for Clinical Benchmarks

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Stress-Testing EEG Foundation Models for Clinical Decoding: Dataset Identity and Targeted Negative Controls