CachedSearch: Training-Free Cached Exploration for Test-Time Search in Video Diffusion
Test-time search lets small video diffusion models rival larger ones, but costs 2-10x more. All candidates are fully denoised, although most are discarded. Training-free caching makes each rollout 2-3x faster at near-lossless quality. Composition is safe only if lossy caching preserves verifier rankings. We present the first study of whether caching corrupts candidate ranking in video test-time search. On Wan2.1-T2V-1.3B with an adaptive caching wrapper (~2x per-candidate speedup), ImageReward scores seed-matched cached and full rollouts. Median per-prompt Spearman rank correlation is 0.905, with 72% top-1 agreement on the VBench suite. VBench-2.0 replicates this result on a harder suite....
| Authors | Shreshth Saini, Neil Birkbeck, Yilin Wang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 July 2026 |
| Last updated at source | 30 July 2026 |
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