TraceGate: Routing-Action History for Block Reuse in Video Diffusion

Video diffusion transformers repeatedly evaluate costly block stacks and attention routes. Block caching skips stack evaluations; sparse attention reduces work within executed stacks. TraceGate connects these decisions: a planner reuses, repairs, or refreshes query and key clusters on executed calls, and its historical actions inform later residual reuse at the block level. The outer gate combines this delayed feedback with conditioning drift and residual magnitude history; skipped calls do not compute their own attention. A product quantization shortlist reduces planner candidate scoring. Settings focused on efficiency achieve 3.36×, 2.45×, and 3.02× overall speedups on Wan 2.1, Wan 2.2, and HunyuanVideo, respectively, with tradeoffs in task quality. On the Wan 2.1 calibration cohort of 108 videos, the setting with feedback has 0.13 dB higher mean PSNR and 0.003 higher mean SSIM than a retuned setting without feedback; both speedups round to 3.30× and LPIPS is equal at reported precision. This comparison is exploratory because the cohort also informed calibration. Substituting a stale map on 72 selected events tests propagation of inner routing error, not the outer execution versus reuse action.