其中reasoning作为推理模块,帮助模型归纳,跟踪和更新动作规划,acting和环境交互收集更多信息(reasoning traces help the model induce, track, and update action plans as well as handle exceptions, while actions allow it to interface with and gather additional information from external sources such as knowledge ...
提出了一种新的方法——ReAct,它是一种 prompt-based 范式,旨在结合大型语言模型的推理(reasoning)和行动(acting)能力,以解决各种语言理解和决策制定任务。ReAct 通过生成推理痕迹和任务特定行动,并在执行任务时进行动态推理和从外部环境中获取信息。 展示了ReAct 在多个任务上的有效性,包括 HotpotQA、Fever、ALFWorld...
做agent工作一定会看到 ReAct,SelfASk等 范式相关工作,其中ReAct 范式具有影响力的一篇文章: ReAct: Synergizing Reasoning and Acting in Language Models 原文链接: https://ar5iv.labs.arxiv.org/html/2210.03629ar5iv.labs.arxiv.org/html/2210.03629 论文创新点是,使用LLMs 以交互式生成 方式 依次进行...
对于reasoning数据集,benchmark数据有响应变量 思维链: observation的概念是什么? 在概念上理解为环境条件,但是实现时发现是作为LLM的语言输出。 论文的观点:结合推理和行动可以得到更优的效果 分论点: 1.推理reasoning对于行动acting的指导作用(在推理任务上ReAct优于Act) 2.reasoning对于more informed acting的作用?(不...
论文速览【LLM-agent】——【ReAct】Synergizing Reasoning and Acting in Language Models,本文介绍LLM-agent领域的经典方法ReAct,它将LLM的自然语言推理能力和动作生成能力结合,使其同时适用于各类NLP和控制任务,并起到1+1>2的效果
在知识密集型推理(KNOWLEDGE-INTENSIVE REASONING TASKS)任务中,ReAct表现接近COT,远优于Standard,最好的是COT-SC + ReAct: COT中幻觉严重、插入推理和Action之后的结果提升了真实性但限制了推理步骤的灵活性、搜索到有用信息对ReAct至关重要。 ReAct和Act finetune效果最好,且有扩展性: ...
GPT-3 prompting code for ICLR 2023 paper ReAct: Synergizing Reasoning and Acting in Language Models. To use ReAct for more tasks, consider trying LangChain's zero-shot ReAct Agent. Setup You need to first have an OpenAI API key and store it in the environment variable OPENAI_API_KEY (see...
This repository contains the implementation of the ReAct: Synergizing Reasoning and Acting in Language Models, which is a model that combines reasoning and acting capabilities in language models. The approach is based on the idea of combining reasoning and acting capabilities in language models to ena...
Behaving efficiently and flexibly is crucial for biological and artificial embodied agents. Behavior is generally classified into two types: habitual (fast but inflexible), and goal-directed (flexible but slow). While these two types of behaviors are typ
ReAct: Synergizing Reasoning and Acting in Language Modelsarxiv.org/abs/2210.03629 在论文的开头作者放了一张对比图 图一:(1)为用户给出的问题,有三种提示方式:(1a)标准;(1b)CoT(仅推理);(1c)仅行动;(1d)ReAct(推理+行动)。可以看到前三者的答案都不准确,(1d)的回答更加准确。 图二:用(2a)仅...