SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models

1 January 2024

Papers citing "SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models"

7 / 7 papers shown

Title
Private Transformer Inference in MLaaS: A Survey Yang Li Xinyu Zhou Yishuo Wang Liangxin Qian Jun Zhao 21 0 0 15 May 2025
A Survey on Privacy Risks and Protection in Large Language Models Kang Chen Xiuze Zhou Yuanguo Lin Shibo Feng Li Shen Pengcheng Wu AILaw PILM 147 0 0 04 May 2025
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private Large Language Model Inference Wenxuan Zeng Ye Dong Jinjin Zhou Junming Ma Jin Tan Runsheng Wang Meng Li 49 0 0 12 Jan 2025
Privacy in Large Language Models: Attacks, Defenses and Future Directions Haoran Li Yulin Chen Jinglong Luo Yan Kang Xiaojin Zhang Qi Hu Chunkit Chan Yangqiu Song PILM 45 42 0 16 Oct 2023
Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole Sentence Haoran Li Mingshi Xu Yangqiu Song 87 45 0 04 May 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 313 11,953 0 04 Mar 2022