Intrinsic Distribution Matching
Read the original on arXiv AI →Intrinsic Distribution Matching (IDM) extends distribution matching distillation (DMD) for one‑step and few‑step text‑to‑image generation by adding an explicit moment constraint that matches feature means and per‑coordinate standard deviations using the generator’s exponential‑moving‑average copy. This approach avoids a separate fake‑score network and an external feature encoder, while retaining the full DMD correction. Experiments on Z‑Image‑Turbo 6B and Qwen‑Image 20B with full‑parameter and LoRA tuning show IDM achieving the highest scores on Chinese and English LongText‑Bench, and ablations confirm the benefit of the moment loss.
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