—— Future of prompt engineering:Michael Figueroa 本图由Bing使用DALL· E人工智能创作 Michael Figueroa(Toptal资讯安全服务资深策略总监,生成式 AI 网络安全专家)在解释提示工程时,指出提示工程并不是从模型的输出中提取或简化信息,而是试图深入理解“语言模型”如何与特定的“语言提示”相关联。 换句话说,关注的...
看起来很高大上,其实具体实现就是prompt engineering,要根据具体任务写好prompt,在prompt里写清楚推理过程每个想法的粒度,让语言模型按照prompt内容逐步推理,依次生成中间想法。例如前面CoT prompt里第一个样例中的4 + 8 = 12 (left: 4 6 12)就是一个最基础的想法。 3.2 Thought generator 如何根据当前状态生成候...
The integration of Artificial Intelligence (AI) into robotic arms, particularly through the use of Large Language Models (LLMs), marks a significant advancement in automation, enabling these devices to perform complex tasks with unparalleled precision. Despite the potential of LLMs to revolutionize ...
ToT represents the problem-solving process as search over a tree, where each node is a "thought" — a coherent chunk of text representing an intermediate reasoning step. This allows the LLM to explore multiple reasoning paths and evaluate the progress of different thoughts towards solving the p...
例子一:【创意文本生成】thought生成方法:直接用COT方法提出多个Plans 原则二:当thought空间比较小【例如只有几个字(字谜游戏),或者只有一行(24点游戏)】 => 使用“propose prompt”依次提出想法,例如下面两个例子: 【24点游戏】是什么?:"Game of 24"是一种数学益智游戏,旨在通过组合和计算四个给定的数字(通常是...
Thought generation:After defining what constitutes a thought, the next step is to determine how these thoughts are generated. The framework proposes two primary techniques.[4] Sampling:This technique involves generating several thoughts independently by using the same prompt. It works best when the th...
然而,使用代表思想的 PAL 公式作为代码,这使得很难解决我们在本文中考虑的创造性写作等具有挑战性的任务。因此,我们的 Tree-of-Thought 公式更通用的任务,并处理 GPT-4 仅使用标准提示实现了非常低的准确度的具有挑战性的任务。 总结: 此外,ToT 等搜索方法比采样方法需要更多的资源(例如 GPT-4 API 成本),以提...
代码:https://github.com/princeton-nlp/tree-of-thought-llm 提出了一个关于语言模型(LM)的新框架:Thought of Tree(ToT),旨在让LM在解决问题时能够进行更加系统和有目的的规划。 作者指出,虽然现有的LM可以执行各种任务,但它们仍然采用了最初的自回归生成文本的机制,即逐个决策地生成文本。
tree of thoughts method. Each expert will share their thought process in detail, taking into account the previous thoughts of others and admitting any errors. They will iteratively refine and expand upon each other's ideas, giving credit where it's due. The process continues until a conclusive...
--method_evaluate (choices=[value, vote]): state evaluator, whether to use the value states independently (used in Game of 24) or vote on states together (used in Creative Writing) --n_generate_sample: number of times to prompt for thought generation --n_evaluate_sample: number of times...