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On-policy distillation is massively data-overfed: a single training prompt recovers most full-dataset performance gains, while just 16 prompts saturate 98.9% of reachable state space to match full-data distillation.
RailSyn achieves up to 4.9 points improvement in RFOD detection accuracy by intelligently generating synthetic data that addresses specific task deficiencies.
RailGen reduces the object pixel area by up to 58x, enabling a leap in detection accuracy for small-scale foreign objects in railway safety applications.
