Papers by Mohamed Elmahallawy

1 papers
SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs (2026.acl-long)

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Challenge: Existing privacy defenses reduce leakage of PII due to LLM memorization, but often degrade downstream performance.
Approach: They propose a privacy-aware federated fine-tuning framework for large language models that provides fine-grained privacy control without sacrificing utility.
Outcome: The proposed framework reduces PII leakage while providing fine-grained privacy control without sacrificing utility.

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