VVS accelerates visual AR image generation by partially skipping verifications in speculative decoding, achieving 2.8x fewer target forward passes while preserving competitive quality.
Gans trained by a two time-scale update rule converge to a local nash equilib- rium
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.CV 2years
2025 2representative citing papers
FlashLips delivers 100+ FPS mask-free lip-sync by reconstructing target frames in latent space from an audio-predicted lips-pose vector using a compact U-Net trained solely on reconstruction losses and self-supervised mask removal.
citing papers explorer
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VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping
VVS accelerates visual AR image generation by partially skipping verifications in speculative decoding, achieving 2.8x fewer target forward passes while preserving competitive quality.
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FlashLips: 100-FPS Mask-Free Latent Lip-Sync using Reconstruction Instead of Diffusion or GANs
FlashLips delivers 100+ FPS mask-free lip-sync by reconstructing target frames in latent space from an audio-predicted lips-pose vector using a compact U-Net trained solely on reconstruction losses and self-supervised mask removal.