This paper studies the paradigm of tool learning with foundation models. We ﬁrst recapitulate the cognitive
origins of tool use in human history and categorize tools from the perspective of the user interface. Then we
review the AI paradigm shift brought about by foundation models and discuss the complementary roles of tools
and foundation models, followed by a comprehensive literature review for existing exploration in tool learning.
We formulate a general tool learning framework and highlight core research problems such as bridging user
intents with appropriate tools, better planning by leveraging the reasoning abilities of foundation models,
training strategies for tool learning, and how to facilitate generalization for tool learning. We experiment
with 17 representative tools and demonstrate that current foundation models showcase dexterity and ﬁnesse in
tool use. Finally, we discuss important research topics, including safe and trustworthy tool learning, AI tool
Tool Learning with Foundation Models