TL;DR Teaching Qwen3 models (1.7B-8B) tool selection over 10,000+ tools with RL beats prompting the 402B Llama-4-Maverick on the same job. Title: Training Small Language Models for Transferable Tool Selection URL: Key points ・🧩 Plan-Retrieve-Select: split the instruction into substeps, retrieve candidates, pick one tool per substep ・🧹 Noisy ToolBench G3 gold labels are filtered with a teacher model down to 20,093 examples ・🎯 SFT then GRPO: rank-weighted F1 for Plan, exact match for Select ・📈 ToolBench G3 success: 41.5% at 8B vs. 30.6% for the best prompted Maverick ・🔁 Swap BM25 for the dense retriever COLT and accuracy improves with no retraining ・🧪 A learned selector adds about 13 points over a BM25 top-1 rule ・⚠️ Planning transfers poorly to TaskBench, where a large prompted model still wins A good example of why a small, purpose-trained model can beat a giant prompted one on cost, speed and accuracy. #LLMAgents# #ToolUse#