NaviCache: Test-Time Self-Calibration Caching for Video Generation

• URL: http://arxiv.org/abs/2606.26795v1
• Date: Thu, 25 Jun 2026 09:28:12 GMT
• Title: NaviCache: Test-Time Self-Calibration Caching for Video Generation
• Abstract summary: NaviCache is a test-time self-calibration method for Video Diffusion Models.<n>It bridges the fundamental domain gap and the non-stationary nature of diffusion.<n>It provides a theoretically grounded mechanism for error-bounded skipping.
• Score: 82.90113757454375
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Video Diffusion Models (VDMs) is constrained by immense computational costs. While offline calibration-based acceleration suffers from calibration data dependency, prohibitive calibration duration, and susceptibility to distribution shifts, offline calibration-free methods eliminate these hurdles. However, since they rely on instantaneous zero-order approximations where the mapping between input and output differences varies in real-time, they are susceptible to observational noise and ignore the intrinsic momentum within the diffusion trajectory. In this paper, we propose NaviCache, a plug-and-play test-time self-calibration method re-conceptualizing feature evolution as an Inertial Navigation System (INS) problem. NaviCache bridges the fundamental domain gap and the non-stationary nature of diffusion by modeling the relative coupling between input and output variations. We introduce a dual-state estimation architecture that adaptively tracks the feature change ratio and its latent drift, initialized via a specialized Initial Alignment phase. By integrating a time-dependent noise schedule with an uncertainty-aware Measurement Update mechanism, NaviCache provides a theoretically grounded mechanism for error-bounded computation skipping. Extensive experiments on the HunyuanVideo, Wan, and Open-Sora series demonstrate that NaviCache exhibits more accurate error judgment for computation skipping and achieves outstanding comprehensive performance.

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