ReWorld: An Interactive World Model with Long-Horizon Memory

Published
Source
arXiv
Paper number
994
Field
AI / General
arXiv ID
2608.23565

Key points

  • It mixed attention-window sizes across heads and assigned them randomly at each step so that control is learned through short windows and memory through long windows.
  • At inference, it discards the full history and fills a fixed KV cache from a landmark bank retrieved by camera pose.
  • LoRA distillation reduced sampling to four steps, allowing a single backbone to handle both a high-quality multi-step mode and a real-time interactive mode, producing 704x1280 video in real time.
  • It ranked highest in both control accuracy (rotation error of 11.95 degrees) and visual quality among 6 recent interactive world models.
  • However, because memory is retrieved solely by camera pose, the paper leaves extending memory to dynamic scenes and interactions beyond movement as future work.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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