Simple Alignment for Pixel-Space JiT: Matched Controls and Low-Rank Targets

Simple early-layer representation alignment is a strong baseline for pixel-space JiT on ImageNet-256. With a training-only MLP head, searched FID-50K improves from 4.80 ± 0.16 to 3.69 ± 0.06 across three matched training seeds, a 23.1% reduction. The benefit persists at every common guided CFG scale tested in two complete sweeps and is corroborated by one fixed-CFG pair in the released PixelREPA implementation. Attachment matters: the final-block endpoint is harmful in two seeds. Mean-preserving rank-32 PCA targets retain approximately 87% of the searched-FID gain over two seeds, despite retaining only 26.5% of centered teacher variance. A single random rank-32 basis reaches a similar searched endpoint with 4.2% variance, without establishing equivalence between subspaces. Analysis of the cosine objective separates variance retention, target direction, and conditional predictability; it supplies testable hypotheses rather than a causal account of generation quality. These results support including simple early alignment in matched JiT evaluations and show that much of its measured benefit survives restricted teacher targets.