清華最新研究大幅提升Llama2通用智能體能力,直逼GPT-4水平
["清華大學最新研究提出AgentTuning方法,可以增強LLM的智能體能力。","構建了AgentInstruct智能體數據集,包含高質量的交互軌跡和CoT推理鏈。","採用混合指令微調策略,使用AgentInstruct與通用指令進行聯合微調。","結果表明,AgentLM明顯優於Llama 2,在held-in和held-out任務中表現出色。","70B版本的AgentLM在智能體任務上與GPT-3.5-turbo相匹配,提供開源替代方案。"]
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