Researcher Uses Agents to Scale 100 Labels into 10K Training Samples

A researcher shared a workflow where roughly 100 manually labeled samples are expanded by agents into 10,000 pseudo-labeled examples for model training, arguing this is simpler than direct fine-tuning.

2026-10-08 ~ 2026-10-08 · 2 related posts

• Researcher's agent workflow: label 100 examples, have the agent scale to 10k pseudo-labels — ducha_aiki · 2026-10-08
• Researcher's labeling workflow: hand-label 100 examples, let an agent scale to 10,000 — ducha_aiki · 2026-10-08