Action QFormer Improves Vision-Language-Action Models by Shaping Representations Under Action Supervision

Jul 17, 2026

Researchers present Action QFormer, a query-based interface that reorganizes multimodal information into action-facing representations prior to action generation in vision-language-action (VLA) models. In zero-shot sim-to-real navigation tasks, Action QFormer increases average closed-loop task success from 18.8% to 56.3% and action-generation correctness from 22.5% to 75.5%. The approach reduces destabilization of language-side representations caused by direct action supervision and nearly eliminates out-of-distribution instruction generations.

Why it matters: This work offers a principled method to improve VLA model performance by addressing the trade-off between action supervision and representation stability, advancing beyond reliance on stronger pretrained backbones.

Full story at: arXiv AI/ML ↗