Where to Look Is Not How to Fix: Pre-Denoising Diagnostics and Modality-Dependent Control in Diffusion Composition

Text-to-image diffusion models fail on semantically rare attribute–object compositions, but it is unclear whether this brittleness arises during denoising or is already present in conditioning representations. We study this question at three levels of granularity. First, using a controlled stress protocol across SD1.5, SDXL, and SD3, we show that a Compositional Stress Index derived from text-side non-factorization residuals separates anchor from stress prompts with perfect discrimination (AUC$=1.0$) cross-model, establishing a robust pre-denoising risk axis. Second, embedding-level low-rank repair reduces representation residuals without any positive semantic improvement, while a downstream cross-attention intervention succeeds on the same subset—a site-sensitive boundary between diagnosis and control. Third, we decompose this boundary at block-group resolution under three intervention modalities. Diagnostic accessibility peaks at the deep encoder (D2) across all conditions, but token-level intervention of either sign produces no measurable improvement at any block. Only broad cross-attention ablation moves semantics at D2, while decoder blocks respond to selective boost and collapse under ablation. Together, these results establish that compositional defects are diagnosable before denoising, but where to look is not how to fix: the diagnostic site and the control site require different intervention modalities, and even at the correct site, the wrong modality is futile.