Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully implemented environments with executable APIs and realistic, pre-populated backend databases, creating a major bottleneck for scalability. To overcome this, we propose an...
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🔧 Environment-free Synthetic Data Generation for API-Calling Agents
⏱️ vor 5d 20h (21.07.2026 um 02:00 Uhr) 📂 🔧 AI Nachrichten 📡 Feed 🔗 Quelle: machinelearning.apple.com