Google Research Releases ToolGrad: Answer-First Framework Hits 99.8% Pass Rate for Tool-Use Data Generation

Google Research released ToolGrad, an ACL 2026 Findings framework that generates tool-use datasets by building a verified API chain first and then writing the matching user query, reaching a 99.8% pass rate on ToolBench versus 63.8% for DFS search. Gemma-3-12B fine-tuned on only 500 ToolGrad samples scored 83.1 on BFCL, close to Gemini 2.5 Pro's 83.2. The code, dataset, and models are public under Apache-2.0.

Google Research has released ToolGrad, an ACL 2026 Findings framework that inverts tool-use dataset generation: it builds a verified API chain first, then writes the matching user query. Guided by textual "gradients" from a 4-module propose-execute-select-update loop, ToolGrad reaches a 99.8% pass rate on ToolBench versus 63.8% for DFS search. Gemma-3-12B fine-tuned on only 500 samples scores 83.1 on BFCL, next to Gemini 2.5 Pro at 83.2. Code, dataset, and models are public under Apache-2.0. The post Google Research Releases ToolGrad: Answer-First Framework Hits 99.8% Pass Rate for Tool-Use Data Generation https://www.marktechpost.com/2026/09/10/google-research-releases-toolgrad-answer-first-framework-hits-99-8-pass-rate-for-tool-use-data-generation/ appeared first on MarkTechPost https://www.marktechpost.com .