# VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon

Page: https://stenobird.com/podcast/daily-paper-cast-7079649/vla-corrector-lightweight-detect-and-correct-inference-for-adaptive-action-horizon
Text version: https://stenobird.com/podcast/daily-paper-cast-7079649/vla-corrector-lightweight-detect-and-correct-inference-for-adaptive-action-horizon.md
Podcast: [Daily Paper Cast](https://stenobird.com/podcast/daily-paper-cast-7079649)
Published: 2026-07-07T03:28:20+00:00
Episode link: https://share.transistor.fm/s/69880cac
Audio file: https://media.transistor.fm/69880cac/dc36b2f2.mp3
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JSON: https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/vla-corrector-lightweight-detect-and-correct-inference-for-adaptive-action-horizon
Duration seconds: 1229

## Resource

🤗 Upvotes: 23 | cs.RO Authors: Yi Pan, Miao Pan, Qi Lu, Jiaming Huang, Man Zhang, Siteng Huang, Xin Li, Jie Zhang, Yongliang Shen, Xuhong Zhang, Wenqi Zhang Title: VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon Arxiv: http://arxiv.org/abs/2607.01804v1 Abstract: Vision-Language-Action (VLA) foundation models have recently achieved strong progress in embodied intelligence. To reduce policy-call frequency while preserving temporal coherence, most generative policies adopt an action chunk mechanism, executing multiple future actions in an open-loop manner under a fixed action horizon. However, this "predict-then-blindly-execute" paradigm sacrifices closed-loop reactivity: in contact-rich physical interactions, even small local perturbations can rapidly amplify within the open-loop blind spot, leading to compounding errors and ultimately task failure. To address this limitation, we propose VLA-Corrector, a lightweight corrective inference framework for action-chunked VLA policies. Without modifying the backbone policy weights, VLA-Corrector introduces a lightweight Latent-space Vision Monitor (LVM) that continuously compares predicted and actual visual feature evolution, enabling online detection of visual dynamics deviations. Once persistent deviation is detected, the system triggers a truncation event, discards the remaining stale actions, and invokes corrective replanning via Online Gradient Guidance (OGG). The detect-and-correct mechanism of VLA-Corrector naturally induces an event-triggered adaptive action horizon: it preserves long-horizon execution when the current chunk remains reliable, and invokes short-horizon corrective replanning when execution begins to drift. In doing so, VLA-Corrector mitigates the trade-off imposed by st…

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