Robust Bimanual Vision-Language-Action Models via Embarrassingly Simple Modality Masking
Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that they can still exhibit discontinuous actions and execution failures in complex dual-arm tasks. We hypothesize that unstable multi-view and language fusion is one contributing factor in these failures, often coinciding with attention spreading to distracting regions. To improve robustness, we introduce the Modality Masking Mechanism (M3), an embarrassingly simple, training-only strategy that requires no architectural changes or large-scale robot pretraining. M3 stochastically masks subsets of modality channels during training, exposing the po...
| Authors | Dongzhou Cheng, Ziang Li, Yixiao Zhou et al. |
|---|---|
| Primary category | cs.RO |
| Published | 23 August 2026 |
| Last updated at source | 23 August 2026 |
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