2 citations · 3 across the 4 of their papers we have counts for
4 papers
MAPS: A Multilingual Benchmark for Agent Performance and Security
Omer Hofman, Jonathan Brokman, Oren Rachmil +7
Agentic AI systems, which build on Large Language Models (LLMs) and interact with tools and memory, have rapidly advanced in capability and scope. Yet, since LLMs have been shown t…
X-Detect: Explainable Adversarial Patch Detection for Object Detectors in Retail
Omer Hofman, Amit Giloni, Yarin Hayun +4
Object detection models, which are widely used in various domains (such as retail), have been shown to be vulnerable to adversarial attacks. Existing methods for detecting adversar…
Seeds Don't Lie: An Adaptive Watermarking Framework for Computer Vision Models
Jacob Shams, Ben Nassi, Ikuya Morikawa +3
In recent years, various watermarking methods were suggested to detect computer vision models obtained illegitimately from their owners, however they fail to demonstrate satisfacto…
First to Possess His Statistics: Data-Free Model Extraction Attack on Tabular Data
Masataka Tasumi, Kazuki Iwahana, Naoto Yanai +5
Model extraction attacks are a kind of attacks where an adversary obtains a machine learning model whose performance is comparable with one of the victim model through queries and…