ReWeight: Leveraging Human Data for VLA Post-Training via Demonstration Retrieval and Sample Weighting
Post-training vision-language-action (VLA) models for specific robots and tasks requires in-domain demonstrations, yet collecting diverse robot data is costly. Egocentric human demonstrations provide a scalable alternative, but directly mixing human and robot data can introduce cross-embodiment discrepancies and degrade policy performance. To address this challenge, we introduce ReWeight, a framework that incorporates human data into VLA post-training through demonstration-level retrieval and sample-level weighting. ReWeight learns a cross-embodiment visuomotor representation that combines visual observations with future actions to measure behavioral similarity between human and robot dem...
| Authors | Chenwei Wang, Dianye Huang, Match W. L. Ko et al. |
|---|---|
| Primary category | cs.RO |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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