405rar May 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

: A framework proposed in early 2026 that uses "Rationale-Augmented Retrieval" to reduce hallucinations and improve query formulation in AI agents. AI responses may include mistakes. Learn more [2411.00776] Randomized Autoregressive Visual Generation It is important to distinguish the image generation

: The paper and its associated codebase are available through platforms like arXiv and GitHub . Related Benchmarks & Agents AI responses may include mistakes

: On the ImageNet-256 benchmark, RAR achieved a FID score of 1.48 , which is a significant improvement over previous autoregressive generators and even outperforms many top-tier diffusion-based and masked transformer models.