# AnchorQ uses flow-reversed action anchors to improve RL sample efficiency for robot policies

- Source: arXiv cs.RO
- Published: 2026-10-19T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/d9uduswcvxotizyiaz9l6gze8
- Original: https://arxiv.org/abs/2610.22852

## Summary

An arXiv paper proposes AnchorQ, which uses flow reversal to map reference policy behaviors into state-conditioned latent anchors, samples particles near the anchors, and applies value-guided sampling to achieve coarse-to-fine policy improvement. The analysis shows that anchors reduce identification complexity but introduce support bias; particle refinement trades this bias against action-class complexity, and critic accuracy determines the reliability of KL-regularized value-guided selection.