ODC: Orthogonal Drift Correction for Improved Text-to-Image Semantic Alignment at Inference

The paper introduces Orthogonal Drift Correction (ODC), an inference-time guidance method that mitigates semantic drift in text-to-image generation without retraining or extra user input. ODC operates in two stages: first it detects drift by comparing the generated image to the prompt in a shared vision-language embedding space, isolates the orthogonal component of the drift, and converts it back into text; second it refines the text conditioning for a second generation pass using an adaptive rank-reduced concept removal module. Experiments show ODC improves prompt-image alignment, raising CLIP scores by up to 5.4% on COALBench-300 and PartiPrompts, and boosting the 3-in-1 score by 4.5% on T2I-CompBench’s complex subset.

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• rag
• diffusion
• multimodal
• benchmarks
• safety