BayesFP provides a unified retraining-free sampler for diffusion and flow policies by casting constrained trajectory generation as posterior sampling via an extended Feynman-Kac corrector.
arXiv preprint arXiv:2603.10052 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
SafeVLA-Bench adds STL-based safety checks to VLA benchmarks and finds 13-56% of successful rollouts on LIBERO and RoboCasa-365 violate at least one safety clause.
COAST applies contrastive conceptors to steer VLA hidden states into task-specific success subspaces, yielding over 20% simulation and 40% real-robot success rate gains across three distinct policies.
citing papers explorer
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BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling
BayesFP provides a unified retraining-free sampler for diffusion and flow policies by casting constrained trajectory generation as posterior sampling via an extended Feynman-Kac corrector.
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SafeVLA-Bench: A Benchmark for the Success-Safety Gap in Vision-Language-Action Models
SafeVLA-Bench adds STL-based safety checks to VLA benchmarks and finds 13-56% of successful rollouts on LIBERO and RoboCasa-365 violate at least one safety clause.
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Contrastive Conceptor Activation Steering (COAST): Unlocking Vision-Language-Action Models through Hidden States
COAST applies contrastive conceptors to steer VLA hidden states into task-specific success subspaces, yielding over 20% simulation and 40% real-robot success rate gains across three distinct policies.