Summary of Toolbridge: An Open-source Dataset to Equip Llms with External Tool Capabilities, by Zhenchao Jin et al.
ToolBridge: An Open-Source Dataset to Equip LLMs with External Tool Capabilities
by Zhenchao Jin, Mengchen Liu, Dongdong Chen, Lingting Zhu, Yunsheng Li, Lequan Yu
First submitted to arxiv on: 8 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The integration of external tools into large language models (LLMs) like GPT-4o and Llama 3.1 enables them to evolve from basic conversational agents to general-purpose assistants. The quality and diversity of training data drive these advancements, but the existing LLMs provide limited transparency regarding their datasets and data collection methods. This research aims to address this limitation by introducing ToolBridge, a dataset construction process that empowers LLMs to learn how to utilize external tools effectively. By fine-tuning on curated data entries, LLMs can invoke external tools in appropriate contexts to improve predictive accuracy for tasks like data processing, numerical computation, and factual retrieval. The experimental results show consistent performance improvements on standard benchmarks and custom evaluation datasets when using ToolBridge. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are getting smarter because they’re learning from lots of different data sources. These models can have conversations with us, but they can also help us do things like add up numbers or find answers to questions. The problem is that we don’t always know how the models learned what they know. This research wants to change that by creating a new way to make language models more transparent and open. They’re calling it ToolBridge, and it’s designed to help language models learn how to use other tools and programs to get even better at their jobs. |
Keywords
» Artificial intelligence » Fine tuning » Gpt » Llama
