most citedAdversarial Robustness for Visual Grounding of Multimodal Large Language Models

2 citations · 3 across the 3 of their papers we have counts for

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cs.CR2025

SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity

Pengfei Jing, Mengyun Tang, Xiaorong Shi +5

Evaluating Large Language Models (LLMs) is crucial for understanding their capabilities and limitations across various applications, including natural language processing and code…

cs.CR2024★ 1 cited

Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models

Yang Bai, Ge Pei, Jindong Gu +2

Large language models (LLMs) have achieved remarkable performance on a wide range of tasks. However, recent studies have shown that LLMs can memorize training data and simple repea…