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Addressable Memory for Video World Models

Research Multimodal & Generative

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Merged summary

TL;DR - WorldTrace is a training-free KV-cache memory framework that keeps interactive video world models able to "remember" and re-render previously seen scenes far beyond their training horizon. It matters because long-horizon visual persistence is a core blocker for interactive/generative world models, and this fixes it without retraining.

  • Diagnoses the failure mode: once rollouts exceed the training horizon, temporal RoPE offsets go out-of-distribution, so attention can no longer address stored frames in the growing KV cache; naive compression in RoPE-rotated space further corrupts memory by averaging incompatible positional phases.
  • Core fix: assign each compressed summary slot a distinct, in-distribution virtual position, keeping the compacted cache addressable.
  • Two compression variants: WorldTrace-Field compresses history for temporal coherence; WorldTrace-Landmark stores verbatim scene traces at detected transitions for episodic recall.
  • Introduces LoopBench (can a compressed cache reconstruct a previously visited scene after a long detour); reports +15.5% temporal consistency (Field) and +19.5% episodic recall (Landmark), all without retraining.

Sources (1)

Addressable Memory for Video World Models

arXiv cs.CV Xindi Wu, Sven Elflein, James Lucas, Olga Russakovsky, Laura Leal-Taixé, Despoina Paschalidou, Jonathan Lorraine, Aljoša Ošep 2026-08-07 arXiv:2608.07408
Public signals Hugging Face upvotes 15
Providers: Hugging Face · Upvotes 15 OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-09 08:18:32.817011 UTC

TL;DR - WorldTrace is a training-free KV-cache memory framework that keeps interactive video world models able to "remember" and re-render previously seen scenes far beyond their training horizon. It matters because long-horizon visual persistence is a core blocker for interactive/generative world models, and this fixes it without retraining.

  • Diagnoses the failure mode: once rollouts exceed the training horizon, temporal RoPE offsets go out-of-distribution, so attention can no longer address stored frames in the growing KV cache; naive compression in RoPE-rotated space further corrupts memory by averaging incompatible positional phases.
  • Core fix: assign each compressed summary slot a distinct, in-distribution virtual position, keeping the compacted cache addressable.
  • Two compression variants: WorldTrace-Field compresses history for temporal coherence; WorldTrace-Landmark stores verbatim scene traces at detected transitions for episodic recall.
  • Introduces LoopBench (can a compressed cache reconstruct a previously visited scene after a long detour); reports +15.5% temporal consistency (Field) and +19.5% episodic recall (Landmark), all without retraining.
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