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Achieving 100x parameter efficiency, LoopWM redefines how we approach long-horizon world modeling by introducing iterative latent depth as a new scaling axis.
Training-free image editing can now beat fine-tuned models, thanks to a clever way of injecting visual context and ensuring concept alignment.
Achieve 7.7% better compression than JPEG-XL by using a bit-depth adaptive entropy model for lossless raw image compression.
Interpolating latent representations before decoding yields a reconstruction FID (iFID) that finally aligns with the generation FID of latent diffusion models, achieving ~0.85 correlation where standard rFID fails.
