Diagnose transformer prediction failures from weights alone, then correct them by retraining one layer. GPT-2 capital-city accuracy 2/8 → 8/8 with zero side effects, achievable through any of attention, FFN, or V-only (590K params).
A redefinition of narrative as the spatiotemporal design of cognitive energy. Same five-dimensional measurement applies across text, music, dance, education, art, architecture, and UI.
We treat deep learning as something you train, not something you fix. That's a habit, not a fact. I edited 590,000 parameters in GPT-2 — half a percent of the model — and corrected six wrong answers without damaging anything else.
딥러닝을 고치는 도구는 늘 '재학습'이었다. 그건 사실이라기보다 습관이다. GPT-2의 0.5%만 한 번 손봐서 틀린 답 여섯 개를 모두 고쳤다. 다른 능력은 그대로다.