117 citations · 191 across the 8 of their papers we have counts for
8 papers
Invitation Is All You Need! Promptware Attacks Against LLM-Powered Assistants in Production Are Practical and Dangerous
Ben Nassi, Stav Cohen, Or Yair
The growing integration of LLMs into applications has introduced new security risks, notably known as Promptware - maliciously engineered prompts designed to manipulate LLMs to com…
Identifying Topological Phase Transitions in Experiments Using Manifold Learning
Eran Lustig, Or Yair, Ronen Talmon +1
We demonstrate the identification and classification of topological phase transitions from experimental data using Diffusion Maps: a nonlocal unsupervised machine learning method.…
Spectral Discovery of Jointly Smooth Features for Multimodal Data
Felix Dietrich, Or Yair, Rotem Mulayoff +2
In this paper, we propose a spectral method for deriving functions that are jointly smooth on multiple observed manifolds. This allows us to register measurements of the same pheno…
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
Or Yair, Felix Dietrich, Ronen Talmon +1
In this paper, we address the problem of Domain Adaptation (DA) using Optimal Transport (OT) on Riemannian manifolds. We model the difference between two domains by a diffeomorphis…
Parallel Transport on the Cone Manifold of SPD Matrices for Domain Adaptation
Or Yair, Mirela Ben-Chen, Ronen Talmon
In this paper, we consider the problem of domain adaptation. We propose to view the data through the lens of covariance matrices and present a method for domain adaptation using pa…
No equations, no parameters, no variables: data, and the reconstruction of normal forms by learning informed observation geometries
Or Yair, Ronen Talmon, Ronald R. Coifman +1
The discovery of physical laws consistent with empirical observations lies at the heart of (applied) science and engineering. These laws typically take the form of nonlinear differ…
Local Canonical Correlation Analysis for Nonlinear Common Variables Discovery
Or Yair, Ronen Talmon
In this paper, we address the problem of hidden common variables discovery from multimodal data sets of nonlinear high-dimensional observations. We present a metric based on local…
CaSCADE: Compressed Carrier and DOA Estimation
Shahar Stein, Or Yair, Deborah Cohen +1
Spectrum sensing and direction of arrival (DOA) estimation have been thoroughly investigated, both separately and as a joint task. Estimating the support of a set of signals and th…