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REFLEXION CARRIERE

LEVIS-Canada

Company Name:
Corporate Name:
REFLEXION CARRIERE
Company Title:  
Company Description:  
Keywords to Search:  
Company Address: 4950 Boul DE LA Rive-Sud,LEVIS,QC,Canada 
ZIP Code:
Postal Code:
G6V4Z6 
Telephone Number: 4188356201 
Fax Number:  
Website:
 
Email:
 
USA SIC Code(Standard Industrial Classification Code):
8331-06 
USA SIC Description:
Career & Vocational Counseling 
Number of Employees:
5 to 9 
Sales Amount:
Less than $500,000 
Credit History:
Credit Report:
Very Good 
Contact Person:
 
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Company News:
  • Reflexion: Language Agents with Verbal Reinforcement Learning
    Reflexion is flexible enough to incorporate various types (scalar values or free-form language) and sources (external or internally simulated) of feedback signals, and obtains significant improvements over a baseline agent across diverse tasks (sequential decision-making, coding, language reasoning)
  • 【论文阅读】Reflexion: 大模型如何从错误经验中学习? - 知乎
    Reflexion框架 如图所示,Reflexion框架包含四个组成部分: Actor: Actor由LLM担任,主要工作是基于当前环境生成下一步的动作。 Evaluator: Evlauator主要工作是衡量Actor生成结果的质量。就像强化学习中的Reward函数对Actor的执行结果进行打分。 Self-reflexion:Self-reflexion一般由LLM担任,是Reflexion框架中最重要的
  • [NeurIPS 2023] Reflexion: Language Agents with Verbal . . . - GitHub
    This repo holds the code, demos, and log files for Reflexion: Language Agents with Verbal Reinforcement Learning by Noah Shinn, Federico Cassano, Edward Berman, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao We have provided a set of notebooks to easily run, explore, and interact with the results
  • Agent 系列之Reflection框架解析_reflexion: language agents with verbal . . .
    文章浏览阅读6 7k次,点赞25次,收藏33次。Reflexion: Language Agents with Verbal Reinforcement Learning论文介绍了一种名为“Reflexion”的新框架,通过反思提高决策能力_reflexion: language agents with verbal reinforcement learning
  • 自我反思(Reflexion) | Prompt Engineering Guide
    自我反思(Reflexion) 自我反思是一个通过语言反馈来强化基于语言的智能体的框架。根据 Shinn et al (2023),“自我反思是一种‘口头’强化的新范例,它将策略参数化为智能体的记忆编码与 LLM 的参数选择配对。” 在高层次上,自我反思将来自环境的反馈(自由形式的语言或者标量)转换为语言反馈
  • Reflexion(反思):让AI自我改进的智能提示技术 | Tipkay
    Reflexion:让AI通过执行任务、评估结果和自我反思来记录经验教训,不断学习改进的提示技术。 本文深入解析相关概念与实践方法,Tipkay是AI提示词工程与Agent实践平台,提供在线练习和智能体案例。通过详细的步骤说明和实战案例,帮助您更好地理解和应用AI技术,提升工作效率和专业技能。适合AI
  • 深入解析Reflexion提示词模式 - AI 数字未来
    本报告旨在对Reflexion提示词模式进行深入而全面的阐述。Reflexion是一种新颖的框架,通过语言反馈而非模型权重更新来强化语言智能体,使其能够通过自我反思和经验记忆来优化决策和行为。报告将详细介绍Reflexion的核心概念、工作原理、关键组件(Actor、Evaluator、Self-Reflection)、迭代自我纠正机制
  • Reflexion | 提示工程指南 lt;!-- -- gt; - 提示工程指南
    Reflexion Reflexion 是一个通过语言反馈强化基于语言的智能体的框架。根据 Shinn 等人 (2023) 的说法,“Reflexion 是一种新的‘语言’强化范式,它将策略参数化为智能体的记忆编码与 LLM 参数选择的配对。” 从宏观上看,Reflexion 将来自环境的反馈(可以是自由形式的语言或标量)转换为语言反馈,也
  • LLM As Agents (4):Reflexion - 知乎
    Reflexion算法框架 Reflexion包含三个模块: Actor (行动者)、 Evaluator (评估器)和 Self-Reflection (自我反思)。 Actor Actor是建立在大型语言模型(LLM)之上的,它专门通过特定Prompt生成所需的文本和动作,这些Prompt是基于状态观察条件的。类似于传统基于策略的RL设置,从当前策略πθ在时间t采样一个动作或
  • Reflexion: 语言智能体的口头强化学习 - 懂AI
    Reflexion是一种创新的框架,通过语言反馈而非权重更新来强化语言智能体。它让智能体对任务反馈进行口头反思,并将反思内容存储在记忆缓冲区中,以改进后续决策。Reflexion在多种任务中显著优于基线智能体,展现了语言反馈在强化学习中的潜力。




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