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English(EN) Chain of Thought Is Now Built In. Should You Still Prompt for It?

思维链提示现已内置于大型语言模型中,减少了对明确指令的需求

思维链(Chain of Thought, CoT)提示,即指示模型“一步一步思考”,通过允许中间步骤被分词,在复杂的推理任务中非常有效。然而,OpenAI等实验室的新模型已将这种推理能力内部集成,使得明确的CoT提示变得冗余甚至有害。Sprague等人的一项元分析等研究表明,CoT的好处在数学和符号推理中最为明显,因为中间状态至关重要,而在分类或提取等任务中则不那么明显。生成冗长的CoT解释的成本可能很高,因为输出令牌成本高昂且会增加显著的延迟。 AI

影响 明确的思维链提示对于先进的大型语言模型来说正变得不那么必要,这可能会降低复杂推理任务的成本和延迟。

排序理由 该条目讨论了(思维链)提示技术相对于大型语言模型能力的演变和有效性,而不是宣布新的模型发布或研究突破。

在 dev.to — LLM tag 阅读 →

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思维链提示现已内置于大型语言模型中,减少了对明确指令的需求

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该条目讨论了(思维链)提示技术相对于大型语言模型能力的演变和有效性,而不是宣布新的模型发布或研究突破。
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  1. dev.to — LLM tag TIER_1 English(EN) · Multigrid ·

    思维链现已内置。您还应该提示它吗?

    <p>Adding <em>think step by step</em> to a prompt was the highest-leverage five words in prompting for about two years. On a model that already reasons before it answers, the same five words buy nothing and may cost you something. The question is how to tell which model you have.…