Signals 4 · free daily AI digest

If at First You Don't Succeed, Backtrack: Lightweight Recovery for Frozen VLAs

Paper recorded by Signals 4 on 2026-10-23 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26

Category: cs.LG · 机器学习 · first seen 2026-10-26

Abstract

Vision-Language-Action (VLA) models perform well on robotic manipulation, yet remain brittle once their own actions carry them into states their training data barely covers. Recovering from such failures usually requires recovery demonstrations, policy retraining, or a separate model at inference time. We introduce Backtrack, a lightweight failure detection and recovery mechanism for frozen VLAs t

Read on arXiv →

#180 most recent of 749 cs.LG papers we have recorded · ↑ newer: Knowledge Distillation across Item and Code Spaces for Parallel Genera · ↓ older: Learning Positive Linear Combinations of ReLUs in Fully Polynomial Tim
Cite this page: If at First You Don't Succeed, Backtrack: Lightweight Recovery for Frozen VLAs: the #180 most recent of 749 cs.LG papers we have recorded (as of 2026-10-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/if-at-first-you-don-t-succeed-backtrack-lightweight-recovery-for-frozen-vlas.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.LG papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions