Summary of Tl-training: a Task-feature-based Framework For Training Large Language Models in Tool Use, by Junjie Ye et al.
TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use
by Junjie Ye, Yilong Wu, Sixian Li, Yuming Yang, Tao Gui, Qi Zhang, Xuanjing Huang, Peng Wang, Zhongchao Shi, Jianping Fan, Zhengyin Du
First submitted to arxiv on: 20 Dec 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 paper proposes a novel framework, TL-Training, to improve the performance of large language models (LLMs) in tool-use tasks. It analyzes three existing LLMs and identifies key limitations in the standard supervised fine-tuning approach. The authors then develop a task-feature-based framework that addresses these issues by mitigating suboptimal training data effects, adjusting token weights, and incorporating a robust reward mechanism. They validate TL-Training using CodeLLaMA-2-7B and evaluate it on four open-source test sets, achieving results comparable to or surpassing other LLMs while reducing the required training data size. Additionally, the method enhances robustness in noisy environments and improves general task performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are super smart computers that can understand and generate human-like text. They’re really good at doing things like answering questions and writing stories. But sometimes they struggle with using tools and following instructions. To help them get better, the authors of this paper did some research on how language models learn from data. They found out that the way we train these models matters a lot! By changing the way we train them, we can make them even better at using tools and doing tasks. The new way is called TL-Training, and it’s like a special recipe for making language models super smart. |
Keywords
» Artificial intelligence » Fine tuning » Supervised » Token
