TILT lets diffusion models nail complex compositional prompts without retraining
TILT introduces a training-free, test-time reward that reshapes diffusion sampling to favor joint presence of all concepts, fixing compositional failures. By leveraging an intrinsic KL-constrained objective, it boosts alignment on T2ICompBench while preserving image quality, all without external supervision.