1 citations · 1 across the 10 of their papers we have counts for
11 papers
RIFT-Bench: Dynamic Red-teaming For Agentic AI Systems
Yarin Yerushalmi Levi, Roy Betser, Amit Giloni +5
Agentic AI systems powered by large language models (LLMs) are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond those of traditional LLM vul…
The Universal Normal Embedding
Chen Tasker, Roy Betser, Eyal Gofer +2
Generative models and vision encoders have largely advanced on separate tracks, optimized for different goals and grounded in different mathematical principles. Yet, they share a f…
Training-free Detection of Generated Videos via Spatial-Temporal Likelihoods
Omer Ben Hayun, Roy Betser, Meir Yossef Levi +2
Following major advances in text and image generation, the video domain has surged, producing highly realistic and controllable sequences. Along with this progress, these models al…
Make it SING: Analyzing Semantic Invariants in Classifiers
Harel Yadid, Meir Yossef Levi, Roy Betser +1
All classifiers, including state-of-the-art vision models, possess invariants, partially rooted in the geometry of their linear mappings. These invariants, which reside in the null…
InfoNCE Induces Gaussian Distribution
Roy Betser, Eyal Gofer, Meir Yossef Levi +1
Contrastive learning has become a cornerstone of modern representation learning, allowing training with massive unlabeled data for both task-specific and general (foundation) model…
AgenTRIM: Tool Risk Mitigation for Agentic AI
Roy Betser, Amit Giloni, Shamik Bose +4
AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper tool permissions introduce security risk…
General and Domain-Specific Zero-shot Detection of Generated Images via Conditional Likelihood
Roy Betser, Omer Hofman, Roman Vainshtein +1
The rapid advancement of generative models, particularly diffusion-based methods, has significantly improved the realism of synthetic images. As new generative models continuously…
Training-Free Policy Violation Detection via Activation-Space Whitening in LLMs
Oren Rachmil, Avishag Shapira, Roy Betser +5
As organizations increasingly deploy LLMs in sensitive domains such as legal, financial, and medical settings, ensuring alignment with internal organizational policies has become a…
Counterfactual-based Agent Influence Ranker for Agentic AI Workflows
Amit Giloni, Chiara Picardi, Roy Betser +3
An Agentic AI Workflow (AAW), also known as an LLM-based multi-agent system, is an autonomous system that assembles several LLM-based agents to work collaboratively towards a share…
Whitened CLIP as a Likelihood Surrogate of Images and Captions
Roy Betser, Meir Yossef Levi, Guy Gilboa
Likelihood approximations for images are not trivial to compute and can be useful in many applications. We examine the use of Contrastive Language-Image Pre-training (CLIP) to asse…
Enhancing Neural Training via a Correlated Dynamics Model
Jonathan Brokman, Roy Betser, Rotem Turjeman +3
As neural networks grow in scale, their training becomes both computationally demanding and rich in dynamics. Amidst the flourishing interest in these training dynamics, we present…