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teamchong
4774aeb14c
Co-render the OCR instruction into the same PNG as the content, delimited by '===…===' bands, with the API system field dropped. L1 OCR fidelity, Opus 4.7, 20 production blocks, 7×10 cell: - baseline (text-only): 97.91% mean / 96.25% min - reflow (separate system): 91.99% mean / 82.59% min (-5.93pp) - reflow-inimage: 98.95% mean / 96.42% min (+1.04pp) reflow-inimage wins on all 20/20 blocks vs reflow, and beats the text-only baseline on 17/20 blocks. Three blocks hit 100%. The -5.93pp reflow regression that the cell-pitch sweep partially recovered disappears entirely when the instruction is co-rendered. Mechanism: when system carries the instruction and the image carries the content, the model does cross-modal binding to figure out what the image is for. Co-rendering reduces it to a single-modal task with an unambiguous parse rule. Files: - eval/eval-l1-ocr.mjs: add reflow-inimage variant + prompt - README.md: new section before history compression - eval/EXPERIMENT_LOG.md: attempt #2 writeup - eval/results/{l1-report.md, l1-results.json}: regenerated