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cs.CR2025
LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation
Abhinav Kumar, George Torres, Noah Guzinski +6
The privacy vulnerabilities of the federated learning (FL) paradigm, primarily caused by gradient leakage, have prompted the development of various defensive measures. Nonetheless,…
cs.CL2025
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models
Haokun Chen, Sebastian Szyller, Weilin Xu +1
Large language models (LLMs) are trained using massive datasets, which often contain undesirable content such as harmful texts, personal information, and copyrighted material. To a…