所以如果存在解读有误的地方,欢迎交流。 参考文献 ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arxiv.org/pdf/2307.1678 github.com/OpenBMB/Tool发布于 2023-08-13 18:35・IP 属地广东 内容所属专栏 自然语言处理NLP论文阅读 自然语言处理,深度学习,NLP, DL 订阅专栏 LLM...
项目网站及代码:ReAct: Synergizing Reasoning and Acting in Language Models 这个也可以看我Agent的笔记 哦另外我看到我的笔记上还有一个不错的可视化 WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings WizMap:用于探索大规模机器学习嵌入的可扩展交互式可视化工具机器学习模型...
Recent research shows the potential of enhancing the problem-solving ability of large language models (LLMs) through the use of external tools. However, prior work along this line depends on the availability of existing tools. In this work, we take an initial step towards removing this dependenc...
Output: Metforministhe first-line drugfor[Retrieval("illness, diabetes, obesity")] patients with type2diabetes and obesity. Input:<REPLACEGPT>Output:"""llmchain_prompt="""Your taskisto complete a given piece of text. You can use a Large Language Model to predict information. You candoso by...
Large language models (LLMs) have revolutionized machine learning and captivated the general public with their remarkable generative abilities and capabilities for solving complex new tasks using only a few examples or text prompts. It is therefore surprising that these seemingly omn...
RoTBench: A Multi-Level Benchmark for Evaluating the Robustness of Large Language Models in Tool Learning - Junjie-Ye/RoTBench
Tool Learning Survey. [Paper] Tool Learning Paper List. [Project] WebCPM. [Paper] Citation Feel free to cite us if you like ToolBench. @misc{qin2023toolllm,title={ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs},author={Yujia Qin and Shihao Liang and Yining ...
Julie Ann Sime
Toolformer 基于带有 in-context learning(ICL)的大型语言模型从头开始生成数据集(Schick and Schütze, 2021b; Honovich et al., 2022; Wang et al., 2022)的思路:只需给出少数几个人类使用 API 的样本,就可以让 LM 用潜在的 API 调用标注一个巨大的语言建模数据集;然后使用自监督损失函数来确定哪些 API ...
论文3:ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios TODO 论文4:TravelPlanner: A Benchmark for Real-World Planning with Language Agents TODO 论文5:ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs TODO ...