most citedAn Empirical Study of the Impact of Federated Learning on Machine Learning Model Accuracy

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cs.CR2026

On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression

Xinwei Zhang, Hangcheng Liu, Li Bai +4

Visual token compression is widely used to accelerate large vision-language models (LVLMs) by pruning or merging visual tokens, yet its adversarial robustness remains unexplored. W…

cs.CR2025

iSeal: Encrypted Fingerprinting for Reliable LLM Ownership Verification

Zixun Xiong, Gaoyi Wu, Qingyang Yu +5

Given the high cost of large language model (LLM) training from scratch, safeguarding LLM intellectual property (IP) has become increasingly crucial. As the standard paradigm for I…