5 papers
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…
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…
AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptation
Itay Nakash, Nitay Calderon, Eyal Ben David +2
Large Language Models (LLMs) have shown impressive versatility as general purpose models. However, their broad applicability comes at a high-cost computational overhead, particular…
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…
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…