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20192026
most citedA Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing

11 citations · 28 across the 25 of their papers we have counts for

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cs.AI2024

Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation

Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo +2

Despite the impressive adaptability of large language models (LLMs), challenges remain in ensuring their security, transparency, and interpretability. Given their susceptibility to…