Real-Time Execution with Autoregressive Policies
Real-time execution, enabled by asynchronous inference that ensures both smooth action trajectories and fast reactivity, is critical for realistic deployments of large-scale Vision-Language-Action models. However, recent work on real-time execution primarily focuses on variants of diffusion policies, even though it is more critical for autoregressive policies given their slower rollout speed in synchronous inference. In contrast, we demonstrate that autoregressive policies can achieve real-time execution by adjusting the tokenization horizon and applying constrained decoding, thereby guaranteeing strict latency bounds that enable multi-trajectory decoding to maximize performance. Across s...
| Authors | Sangkyu Lee, Seohyeon Park, Tackgeun You et al. |
|---|---|
| Primary category | cs.RO |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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