Yan-Tong Liu

VeriVLA: Adaptive Test-Time Verification for Flow-Based VLAs with Latent World Models

Flow-based Vision-Language-Action (VLA) policies are inherently stochastic: different noise seeds can produce action chunks of varying quality from the same observation. At test time, however, the policy typically commits to a single sample without an explicit estimate of its quality. In fine-grained manipulation, exec...