Selective Token-Level Cryptographic Redaction for Privacy-Preserving Clinical Deployment of Large Language Models

ArXi:2606.03399v1 Announce Type: new While large language models (LLMs) are increasingly used for clinical applications, many existing pipelines require sending raw sensitive health information to remote servers for processing, which heightens the risk of privacy leakage. A natural approach to mitigate this risk is to encrypt the data before transmission. However, straightforward solutions such as encrypting the entire dataset