LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

ArXi:2603.14526v1 Announce Type: new The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated by the existence of "golden noise" that enhances video quality, prior work has attempted to improve inference by optimising or searching for better initial noise. However, these approaches have notable limitations: they either rely on priors imposed at the beginning of noise sampling or on rewards evaluated only on the denoised and decoded videos.