Evolution of activation functions for deep learning-based image classification. - Raz Lapid; Moshe Sipper (GECCO Companion, 2022)

An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Convolutional Neural Networks. - Raz Lapid; Zvika Haramaty; Moshe Sipper (Algorithms, 2022)

Attackar: Attack of the Evolutionary Adversary. - Raz Lapid; Zvika Haramaty; Moshe Sipper (CoRR, 2022)

A Melting Pot of Evolution and Learning. - Moshe Sipper; Achiya Elyasaf; Tomer Halperin; Zvika Haramaty; Raz Lapid; Eyal Segal; Itai Tzruia; Snir Vitrack Tamam (GPTP, 2023)

I See Dead People: Gray-Box Adversarial Attack on Image-to-Text Models. - Raz Lapid; Moshe Sipper (PKDD/ECML Workshops (5), 2023)

Patch of Invisibility: Naturalistic Black-Box Adversarial Attacks on Object Detectors. - Raz Lapid; Moshe Sipper (CoRR, 2023)

Open Sesame! Universal Black Box Jailbreaking of Large Language Models. - Raz Lapid; Ron Langberg; Moshe Sipper (CoRR, 2023)

Foiling Explanations in Deep Neural Networks. - Snir Vitrack Tamam; Raz Lapid; Moshe Sipper (Trans. Mach. Learn. Res., 2023)

Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors. - Raz Lapid; Almog Dubin; Moshe Sipper (CoRR, 2024)

XAI-Based Detection of Adversarial Attacks on Deepfake Detectors. - Ben Pinhasov; Raz Lapid; Rony Ohayon; Moshe Sipper; Yehudit Aperstein (Trans. Mach. Learn. Res., 2024)

On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective. - Tao Daniel Alter; Raz Lapid; Moshe Sipper (Trans. Mach. Learn. Res., 2025)

Pulling Back the Curtain: Unsupervised Adversarial Detection via Contrastive Auxiliary Networks. - Eylon Mizrahi; Raz Lapid; Moshe Sipper (CoRR, 2025)

Don't Lag, RAG: Training-Free Adversarial Detection Using RAG. - Roie Kazoom; Raz Lapid; Moshe Sipper; Ofer Hadar (CoRR, 2025)

Losing Control: Data Poisoning Attack on Guided Diffusion via ControlNet. - Raz Lapid; Almog Dubin (CoRR, 2025)