by quchangle1 · LLM Plugin · ★ 481
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Survey: Tool Learning with Large Language Models Recently, tool learning with large language models(LLMs) has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems. This is the collection of papers related to tool learning with LLMs. These papers are organized according to our survey paper "Tool Learning with Large Language Models: A Survey". 中文: We have noticed that PaperAgent and 旺知识 have provided a brief and a comprehensive introduction in Chinese, respectively. We greatly appreciate their assistance. :tada: Our survey paper is accepted by Frontiers of Computer Science (FCS). The latest version of our paper has already been released; please check it out! Please feel free to contact us if you have any questions or suggestions! Contribution :tada::+1: Please feel free to open an issue or make a pull request! :tada::+1: Citation If you find our work helps your research, please kindly cite our paper: ##
| Stars | 481 |
| Forks | 16 |
| Category | LLM Plugin |
| Quality Score | 37.2/100 |
| Open Issues | 2 |
| Last Updated | 2025-08-09 |
| Created | 2024-04-25 |
| Est. Tokens | ~89k |
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LLM-Tool-Survey is This is the repository for the Tool Learning survey.. It is categorized as a LLM Plugin with 481 GitHub stars.
You can find installation instructions and usage details in the LLM-Tool-Survey GitHub repository at github.com/quchangle1/LLM-Tool-Survey. The project has 481 stars and 16 forks, indicating an active community.
The top alternatives to LLM-Tool-Survey on Agent Skills Hub include awesome-llm-powered-agent, DemoGPT, awesome-gpt-prompt-engineering. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.