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Recursive self-improvement in LLMs can lead to unprecedented performance, with Meta^n surpassing all prior agents on challenging benchmarks by leveraging fixed meta-operations.
Agents excel at using tools but falter significantly in navigation, with errors dominating their performance in complex tasks.
