Addressable Memory for Video World Models
- Published
- Source
- arXiv
- Paper number
- 851
- Field
- Computer Vision
- arXiv ID
- 2608.07408
Key points
- We precisely diagnose the cause of long-term memory failure in video world models as distribution shift in positional encoding (RoPE).
- WorldTrace assigns each memory summary a virtual position within the training range, restoring memory accessibility without extra training.
- WorldTrace-Field improves temporal consistency by 15.5%, and WorldTrace-Landmark improves recall of previous scenes by 19.5%.
- We propose LoopBench, a new benchmark that measures whether a model can recover after a long detour back to the original scene.
- It was developed at NVIDIA and can be applied directly to existing models without retraining.
Paper links
External research summaries. These are not HDATF publications or measured product results.