Papers

How we build and measure calibrated classifiers on open-weights language models. Every paper is available as Markdown and PDF, and its results are measured on public data, reproducible with your own API key.

2026

• spinf/moderation: calibrated content moderation from plain-language questions · October 1, 2026, v2 October 7, 2026 (the same pack on Qwen3.8 27B) · PDF · Markdown

  How the moderation prompt-pack turns Gemma 4 12B into a content moderation classifier without fine-tuning: plain-language questions, per-option calibration, calibrated scores for every category and a safe / unsafe decision. Per-category and safe / unsafe results on public datasets, cost, what didn't work, and limitations.