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cs.LG2026
Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach
Guilin Deng, Silong Chen, Yuchuan Luo +6
Federated Large Language Models (FedLLMs) enable multiple parties to collaboratively fine-tune LLMs without sharing raw data, addressing challenges of limited resources and privacy…
cs.LG2026
LEA: Label Enumeration Attack in Vertical Federated Learning
Wenhao Jiang, Shaojing Fu, Yuchuan Luo +1
A typical Vertical Federated Learning (VFL) scenario involves several participants collaboratively training a machine learning model, where each party has different features for th…