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Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models
With the rapid development of Large Language Models (LLMs), we have witnessed intense competition among the major LLM products like ChatGPT, LLaMa, and Gemini.
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering
Federated learning (FL) is becoming a key component in many technology-based applications including language modeling -- where individual FL participants often have privacy-sensitive text data in their local datasets.
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks
This highlights the need to design FL systems that are secure and robust against malicious participants' actions while also ensuring high utility, privacy of local data, and efficiency.
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