Raz Lapid

According to our database, Raz Lapid authored at least 20 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

On the Robustness of Diffusion-Based Image Compression to Bit-Flip Errors.

Amit Vaisman, Gal Pomerants, Raz Lapid

CoRR, April, 2026

BenchOverflow: Measuring Overflow in Large Language Models via Plain-Text Prompts.

Erin Feiglin, Nir Hutnik, Raz Lapid

Trans. Mach. Learn. Res., 2026

2025

Activation Steering for Masked Diffusion Language Models.

Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit LeVi, Raz Lapid

CoRR, December, 2025

Breaking Audio Large Language Models by Attacking Only the Encoder: A Universal Targeted Latent-Space Audio Attack.

Roee Ziv, Raz Lapid, Moshe Sipper

CoRR, December, 2025

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations.

Amit LeVi, Raz Lapid, Rom Himelstein, Yaniv Nemcovsky, Ravid Shwartz-Ziv, Avi Mendelson

CoRR, November, 2025

Losing Control: Data Poisoning Attack on Guided Diffusion via ControlNet.

Raz Lapid, Almog Dubin

CoRR, July, 2025

Don't Lag, RAG: Training-Free Adversarial Detection Using RAG.

Roie Kazoom, Raz Lapid, Moshe Sipper, Ofer Hadar

CoRR, April, 2025

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

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

Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors.

Raz Lapid, Almog Dubin, Moshe Sipper

CoRR, 2024

What's in an AI's Mind's Eye? We Must Know.

Moshe Sipper, Raz Lapid

Computer, 2024

2023

Foiling Explanations in Deep Neural Networks.

Snir Vitrack Tamam, Raz Lapid, Moshe Sipper

Trans. Mach. Learn. Res., 2023

Open Sesame! Universal Black Box Jailbreaking of Large Language Models.

Raz Lapid, Ron Langberg, Moshe Sipper

CoRR, 2023

Patch of Invisibility: Naturalistic Black-Box Adversarial Attacks on Object Detectors.

Raz Lapid, Moshe Sipper

CoRR, 2023

I See Dead People: Gray-Box Adversarial Attack on Image-to-Text Models.

Raz Lapid, Moshe Sipper

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

A Melting Pot of Evolution and Learning.

Moshe Sipper, Achiya Elyasaf, Tomer Halperin, Zvika Haramaty, Raz Lapid, Eyal Segal, Itai Tzruia, Snir Vitrack Tamam

Proceedings of the Genetic Programming Theory and Practice XX [GPTP 2023], 2023

2022

Attackar: Attack of the Evolutionary Adversary.

Raz Lapid, Zvika Haramaty, Moshe Sipper

CoRR, 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

Evolution of activation functions for deep learning-based image classification.

Raz Lapid, Moshe Sipper

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022