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Self-improving agents can evolve autonomously with minimal human input, reshaping our approach to AI adaptability and deployment.
Current memory agents fail to provide reliable governance in shared settings, with no method achieving a balance between utility, access control, and forgetting.
LLM search agents can be easily manipulated, with some models endorsing false claims at alarming rates, revealing a critical gap in their safety evaluation.
