Papers by Chenxi Dai
Stealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack (2025.acl-long)
Copied to clipboard
| Challenge: | Decentralized training is a resource-efficient framework to democratize training of large language models. |
| Approach: | They propose an activation inversion attack to exploit privacy leakage from training data . they construct a shadow dataset comprising text labels and corresponding activations . |
| Outcome: | The proposed attack surface is based on a shadow dataset and public datasets . the proposed attack model reconstructs training data from activations in victim decentralized training. |