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Author

Kang Chen

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Review Open access Aug 2025

Data security in large language models: risks, defense, and directions

Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine translation, and conversational systems. Despite their transformative potential, these models inherently rely on massive amounts of training data, often collected from diverse and...

Kang Chen, Xiu-Ze Zhou, Yuan-Hui Yu et al. · 2 citations
#machine learning Preprint Sep 2026

When Keywords Drop but Classifiers Hold: Soft Refusals under KV Cache Compression

Safety auditing under compression should rely on several judges matched to the serving context rather than on keyword rates alone, because the gap is not universal and weakens under short fillers and paired SnapKV, so safety auditing should rely on several judges matched to the serving context rather than on keyword ra...

Kang Chen, Xiu-Ze Zhou, Hong Chen et al. · 0 citations
Review Open access Aug 2026

Data security in large language models: risks, defense, and directions

This survey offers a comprehensive overview of the main data security risks facing LLMs and reviews current defense strategies, including adversarial training, data cleaning, output guardrails, Reinforcement Learning from Human Feedback, data augmentation, and Retrieval-Augmented Generation (RAG)/agent defenses.

Kang Chen, Xiuze Zhou, Yuanhui Yu et al. · 0 citations

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