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AgentPerturb: Evaluating LLM Agent Robustness under Controlled Interaction Perturbations
Real-world tasks are often complex and noisy, posing substantial challenges for LLM agents. Yet existing evaluations lack a systematic framework for jointly characterizing potential perturbation targets and types. We use this two-dimensional view to conduct a unified study that quantifies the robust
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