Papers by Ateret Anaby Tavor

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Challenge:	Large language models (LLMs) are increasingly deployed as customer-facing agents due to stochastic, multi-turn interactions.
Approach:	They propose a snapshot-based, coverage-guided user simulation framework for efficient and systematic exploration of multi-turn agent behavior.
Outcome:	Experiments on multi-domain benchmarks show that the proposed method improves failure discovery efficiency and task-level coverage compared to standard linear rollout evaluation without increasing overall cost.