Derives optimal inference-time guidance for stochastic interpolant policies via Kolmogorov equation analysis, enabling reactive streaming robot control with training-free and training-based mechanisms.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
TRFP combines rectified flow models with truncation to support multimodal policies in MaxEnt RL while allowing fast one-step sampling and stable training.
citing papers explorer
-
Guided Streaming Stochastic Interpolant Policy
Derives optimal inference-time guidance for stochastic interpolant policies via Kolmogorov equation analysis, enabling reactive streaming robot control with training-free and training-based mechanisms.
-
Truncated Rectified Flow Policy for Reinforcement Learning with One-Step Sampling
TRFP combines rectified flow models with truncation to support multimodal policies in MaxEnt RL while allowing fast one-step sampling and stable training.