JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models
The post-training of Vision-Language-Action (VLA) models is essential due to the diversity of simulators, robot embodiments, and task objectives. Existing compute services, whether offered as direct accelerator rental or batch-workload submission, typically allocate an exclusive set of GPU and CPU resources to a single tenant. While this paradigm maximizes client flexibility, it burdens users with infrastructure adaptation, and the fixed card-hour accounting model renders short or bursty workloads both expensive for tenants and inefficient for the service provider. To address these challenges, we present JoyNexus, a unified service for multi-tenant VLA supervised fine-tuning, reinforcemen...
| Authors | Haoran Sun, Wentao Zhang, Junyang Hua et al. |
|---|---|
| Primary category | cs.DC |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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