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  • 如何看待Meta最近的文章Toolformer? - 知乎
    Meta的Toolformer文章探讨了语言模型如何通过自监督学习掌握外部工具的使用,提升在数学、翻译等任务中的表现。
  • 如何看待Meta最近的文章Toolformer? - 知乎
    HuggingGPT + Toolformer AI天天有大新闻。今天读到: ChatGPT自己会选模型了!微软亚研院+浙大爆火新论文,HuggingGPT项目已开源 这个事情应该和Toolformer以及ChatGPT Plugins联系起来看。下面是Toolformer的一篇介绍: 让ChatGPT长“手”!Meta爆火新论文,让语言模型学会自主使用工具 要点: HuggingGPT利用ChatGPT作为
  • ToolLLM: Facilitating Large Language Models to Master 16000+. . .
    This paper introduces ToolLLM, a whole pipeline for creating and evaluating instruction-tuned language models that can use tools The authors created ToolBench, an instruction-tuning dataset by i) collecting a large number of real-world APIs from multiple categories; ii) creating instructions with seed demonstrations and tool sets; iii) annotate the api call solution paths with ChatGPT They
  • 李宏毅- 生成式AI-New Bing, WebGPT, Toolformer - 知乎
    知乎,中文互联网高质量的问答社区和创作者聚集的原创内容平台,于 2011 年 1 月正式上线,以「让人们更好的分享知识、经验和见解,找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区氛围、独特的产品机制以及结构化和易获得的优质内容,聚集了中文互联网科技、商业、影视
  • TOOLRM: OUTCOME REWARD MODELS FOR TOOL-CALLING LARGE LANGUAGE MODELS
    As large language models (LLMs) increasingly interact with external tools, re-ward modeling for tool use has become a critical yet underexplored area Ex-isting reward models, trained primarily on natural language outputs, struggle to evaluate tool-based reasoning and execution To quantify this gap, we introduce FC-RewardBench, the first benchmark designed to systematically evaluate reward
  • XXH的LLM论文阅读笔记 - 知乎
    Toolformer: 语言模型可以教会自己使用工具 [2302 04761] Toolformer: Language Models Can Teach Themselves to Use Tools (arxiv org) 1 简介 大型语言模型在各种…
  • Mastering Symbolic Operations: Augmenting Language Models with. . .
    Language models' (LMs) proficiency in handling deterministic symbolic reasoning and rule-based tasks remains limited due to their dependency implicit learning on textual data To endow LMs with
  • A API Details - OpenReview
    pic entirely This was corroborated by the fact that increasing 279 the triggering of API calls was observed to decrease the final scores for all QA tasks, and the LLaMA 280 base model already surpassed the GPT-J Toolformer using





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