A Deep-Learning Approach for ECG-Based Cryptographic Key Generation
Learning person-specific 256-bit keys from ECG signals with attention to consistency, separation, and statistical randomness.
Learning person-specific 256-bit keys from ECG signals with attention to consistency, separation, and statistical randomness.
A benchmark for testing whether user-disclosed secrets remain recoverable after a conversation moves to unrelated topics.
Studying harmful agreement in language models and uncertainty thresholds designed to reduce sycophantic responses.
A structured application for comparing model responses with similarity metrics and an LLM judge.
Separating failures to perceive a medical image from agreement with a user’s spatially false premise.