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

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 : A framework proposed in early 2026 that

: 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. It aims to bridge the gap between traditional

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

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