Using Agents and Small Models to Bootstrap Object Detection Data
vanstriendaniel · x · 2026-08-28
The author demonstrates a workflow using agents and small models to train object detectors without labeled data: A zero-shot model (e.g., 0.6B Falcon-Perception) labels samples; a small student model (30M params) learns from it; the student re-scans pages marked "empty" by the teacher, with a VLM judge verifying findings for retraining. After 1-2 iterations, this method extracted 411k illustrations from 115k Britannica pages for $2.
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