Work

ObfusLM: Privacy-preserving Language Model Service against Embedding Inversion Attacks

Year: 2025

Type: conference-paper

Abstract: Yu Lin, Ruining Yang, Yunlong Mao, Qizhi Zhang, Jue Hong, Quanwei Cai, Ye Wu, Huiqi Liu, Zhiyu Chen, Bing Duan, Sheng Zhong. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.18653/v1/2025.acl-long.58

Authors: Yu Lin, Ruining Yang, Yunlong Mao, Qizhi Zhang, Jue Hong, Quanwei Cai, Ye Wu, Huiqi Liu, Zhiyu Chen, Bing Duan, Sheng Zhong

Institution: Nanjing University

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: City University of Hong Kong, National Natural Science Foundation of China, Government of Jiangsu Province, Tsinghua University, Fundamental Research Funds for the Central Universities

Awards: G2379088649, G4961774548, G7344377309, G8583261413

OpenAlex ID: W4412886852

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