Evolving Self-tuning Benchmarks for Long-Horizon Tool Use

arXiv:2610.27307v2 Announce Type: new Abstract: For AI assistants to move beyond simple chat interfaces and reliably assist users with applications like Gmail, Venmo, and Slack, we need to improve their tool-use capabilities. However, existing tool use benchmarks are still limited and difficult to scale because they rely on human supervision or are too domain-specific. To make data generation scalable, we propose, TURTLE (Tool Use Related Tasks with Long-Horizon Evolution), an Unsupervised Environment Design (UED) approach to evolve existing tasks using a proposer, a solver, and a feedback gen

This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.