mark, our method achieves 2.96 gFID with 128
tokens, outperforming VAR (3.3 FID) and FlexVAR (3.05 FID), which both require
680 tokens in their AR models. Moreover, due to the significantly reduced token
count and parallel inference mechanism, our method runs nearly 2x faster
inference speed compared to VAR and FlexVAR. Extensive experimental results
demonstrate DetailFlow's superior generation quality and efficiency compared to
existing state-of-the-art methods.</p>
            
            <p class="paper