405rar Apr 2026

It is important to distinguish the image generation model from other similarly named research:

RAR is an autoregressive (AR) image generator designed to be fully compatible with standard language modeling frameworks. It aims to bridge the gap between traditional AR models and more flexible bidirectional models like diffusion or masked transformers. 405rar

The search for "paper: 405rar" refers to , a recent paper published in November 2024 that introduces a new state-of-the-art model for image generation. Overview of RAR It is important to distinguish the image generation

: It introduces a randomness annealing strategy with a permuted objective . This allows the model to learn bidirectional contexts—seeing different parts of the image simultaneously—without needing extra computational costs or changing the basic autoregressive structure. Overview of RAR : It introduces a randomness

: The paper and its associated codebase are available through platforms like arXiv and GitHub . Related Benchmarks & Agents