Google Research introduces ToolGrad framework for tool-use datasets

Google Research introduced ToolGrad, an efficient framework for generating tool-use datasets that generates ground-truth tool-use chains before prompts, achieving a nearly 100% pass rate and improved LLM tool-use performance.

This update bears on 5 kinds of work in 3 markets. Highest level accepted: L2 Partial automation.

Highest accepted

L2Partial automation

Work

5

Markets

3

Views

90.9K

The work it bears on

Highest level first. Open a kind of work to see everything else that moved it.

• L2Partial automation
  Develop algorithms and study computational propertiesComputing and engineering research
  L2 Partial automationFrom the publisher only
• L2Partial automation
  Build research prototypes and run comparative experimentsComputing and engineering research
  L2 Partial automationFrom the publisher only
• L2Partial automation
  Integrate external systems and data interfacesApplication interfaces and business development
  L2 Partial automationFrom the publisher only
• L2Partial automation
  Implement tool use and agent workflowsModel applications and agent systems
  L2 Partial automationClaimed L3 · Accepted L2From the publisher only
• L2Partial automation
  Build evaluations and regression sets for model applicationsModel applications and agent systems
  L2 Partial automationClaimed L3 · Accepted L2From the publisher only

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