activity
20242026
collaborators

5 papers

cs.AI2026

Efficient Agent Evaluation via Diversity-Guided User Simulation

Itay Nakash, George Kour, Ateret Anaby-Tavor

Large language models (LLMs) are increasingly deployed as customer-facing agents, yet evaluating their reliability remains challenging due to stochastic, multi-turn interactions. C…

cs.MA2025

Effective Red-Teaming of Policy-Adherent Agents

Itay Nakash, George Kour, Koren Lazar +3

Task-oriented LLM-based agents are increasingly used in domains with strict policies, such as refund eligibility or cancellation rules. The challenge lies in ensuring that the agen…

cs.AI2025

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models

George Kour, Itay Nakash, Ateret Anaby-Tavor +1

As Large Language Models (LLMs) become deeply integrated into human life and increasingly influence decision-making, it's crucial to evaluate whether and to what extent they exhibi…

cs.AI2025

How Safe is Your Safety Metric? Automatic Concatenation Tests for Metric Reliability

Ora Nova Fandina, Leshem Choshen, Eitan Farchi +3

Consider a scenario where a harmfulness evaluation metric intended to filter unsafe responses from a Large Language Model. When applied to individual harmful prompt-response pairs,…

cs.CR2024

Breaking ReAct Agents: Foot-in-the-Door Attack Will Get You In

Itay Nakash, George Kour, Guy Uziel +1

Following the advancement of large language models (LLMs), the development of LLM-based autonomous agents has become increasingly prevalent. As a result, the need to understand the…