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Automating code generation, optimizing hybrid Program-of-Thought (PoT)/Chain-of-Thought (CoT)/Tree-of-Thought (ToT) models, incorporating self-verification and self-correction, and adopting PoT into domain-specific applications like logical deduction and scientific discovery can significantly advance the capabilities of LLM-empowered Autonomous Agents.

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