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Distilling LLM agents by supervising semantic actions, not token sequences, unlocks significant performance gains and bypasses tokenization constraints.
SCOUT achieves a remarkable 16.85% improvement in spatial reasoning benchmarks, setting a new standard for Vision-Language Models.