405rar May 2026

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

: A suite released in April 2024 to evaluate how well retrieval models can perform reasoning tasks typically reserved for Large Language Models (LLMs). 405rar

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. It is important to distinguish the image generation

: 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. : On the ImageNet-256 benchmark, RAR achieved a

: 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