most citedStealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CR2025

Merger-as-a-Stealer: Stealing Targeted PII from Aligned LLMs with Model Merging

Lin Lu, Zhigang Zuo, Ziji Sheng +1

Model merging has emerged as a promising approach for updating large language models (LLMs) by integrating multiple domain-specific models into a cross-domain merged model. Despite…

cs.CR2025★ 1 cited

Stealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack

Chenxi Dai, Lin Lu, Pan Zhou

Decentralized training has become a resource-efficient framework to democratize the training of large language models (LLMs). However, the privacy risks associated with this framew…