aiqbenchInformații despre AI & calcul cuantic

...

Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

perspectiva aiqbenchCercetare AI

Google Research's ToolGrad fundamentally improves LLM reliability by inverting the data generation pipeline to prioritize verified tool chains over speculative exploration, achieving a 99.8% pass rate on ToolBench. This approach eliminates wasted compute from failed search paths and allows smaller models like Gemma-3-12B to match frontier performance with minimal fine-tuning. The open-sourced framework offers a practical path for scaling high-quality tool-use datasets without relying on inefficient depth-first search agents.

Sursă care acoperăMarkTechPost

Ce este aceastaLectura unui model asupra articolului și a acoperirii conexe, scrisă pentru aiqbench. Nu sunt cuvintele publicației.

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

MarkTechPost11 septembrie 20264 min de cititArticolul și perspectiva sunt în engleză.

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 appeared first on MarkTechPost.

Training an LLM to call tools reliably requires datasets that pair user queries with correct tool-use chains. Producing that data at scale has been slow and expensive. A team of researchers from Google, the University of Tokyo, RIKEN AIP, and Tohoku University introduce ToolGrad. The research work inverts the usual pipeline: build a verified tool chain first, then write the query. Gemma-3 models fine-tuned on…

Extras afișat conform termenilor RSS ai publicației · 65 cuvinte · textul integral și figurile sunt pe site-ul publicației

Citește pe MarkTechPost ↗Întreabă despre acest articol