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insight - Tool Learning in LLMs
Tool Learning with Large Language Models: A Comprehensive Survey
Large language models (LLMs) benefit significantly from tool learning, which enhances their capabilities in knowledge acquisition, expertise, automation, interaction, interpretability, robustness, and adaptability.
StepTool: Enhancing Large Language Models for Complex Task Solving with Step-Grained Reinforcement Learning
Large language models (LLMs) can be significantly improved in their ability to leverage external tools for complex, multi-step tasks by using a novel step-grained reinforcement learning framework called StepTool.
MetaTool: Enhancing Large Language Models' Ability to Use Tools Through Meta-Task Augmentation
MetaTool is a novel methodology that improves the ability of Large Language Models (LLMs) to effectively utilize tools by incorporating self-supervised learning of "meta-tasks" related to tool understanding, leading to significant performance gains in both tool-oriented and tool-augmented tasks.
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