DecMem: Towards Minute-Long Consistent World Generation with Decoupled Memory

• URL: http://arxiv.org/abs/2605.31336v1
• Date: Fri, 29 May 2026 14:17:59 GMT
• Title: DecMem: Towards Minute-Long Consistent World Generation with Decoupled Memory
• Abstract summary: We move beyond 3D memory and coarse frame-level implicit modeling, and propose a fine-grained, learnable, and scalable memory for consistent world generation.<n>By ensuring precise and efficient long-term memory, DecMem enables minute-level controllable long-term video generation with high-quality extrapolation.
• Score: 44.72702042082084
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent advances in video generative models have promoted rapid progress in controllable world models. However, maintaining fine-grained spatio-temporal consistency under long-horizon reasoning remains a key challenge. In this work, we move beyond explicit 3D memory and coarse frame-level implicit modeling, and propose a fine-grained, learnable, and scalable memory for consistent world generation. We first identify two fundamental limitations of naïve learnable memory architectures in long-horizon extrapolation, namely computational inefficiency and attention dispersion. Through a systematic analysis of attention dispersion, we propose DecMem, a decoupled memory architecture that employs Sparse Global Memory for efficient fine-grained access to global history and Anchored Local Memory for stable and high-quality extrapolation. Extensive experiments demonstrate that DecMem significantly outperforms current state-of-the-art methods. By ensuring precise and efficient long-term memory and achieving superior extrapolation capabilities, DecMem enables minute-level controllable long video generation with high fidelity and consistency.

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