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20242026
most citedTransLinkGuard: Safeguarding Transformer Models Against Model Stealing in Edge Deployment

9 citations · 15 across the 28 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

cs.CR2024

CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models

Naen Xu, Changjiang Li, Tianyu Du +8

Text-to-image diffusion models have emerged as powerful tools for generating high-quality images from textual descriptions. However, their increasing popularity has raised signific…

cs.CR2024★ 1 cited

HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models

Yucheng Zhang, Qinfeng Li, Tianyu Du +4

Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by integrating external knowledge, making them adaptable and cost-effective for various applicatio…

cs.CR2024

CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment

Qinfeng Li, Tianyue Luo, Xuhong Zhang +8

Proprietary large language models (LLMs) exhibit strong generalization capabilities across diverse tasks and are increasingly deployed on edge devices for efficiency and privacy re…

cs.CR2024

DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models

Yanming Liu, Xinyue Peng, Yuwei Zhang +10

Large language models have repeatedly shown outstanding performance across diverse applications. However, deploying these models can inadvertently risk user privacy. The significan…

cs.CR2024★ 9 cited

TransLinkGuard: Safeguarding Transformer Models Against Model Stealing in Edge Deployment

Qinfeng Li, Zhiqiang Shen, Zhenghan Qin +4

Proprietary large language models (LLMs) have been widely applied in various scenarios. Additionally, deploying LLMs on edge devices is trending for efficiency and privacy reasons.…