Policy-Aligned Predictive Verification for Adaptive VLA Action-Chunk Execution
Vision-language-action (VLA) policies generate action sequences that reduce repeated inference, but deciding how much of each sequence to execute is critical to task success. Existing adaptive methods make this decision using generation stability or prediction agreement, yet these signals do not establish whether executing a candidate prefix preserves the ability to complete the task. We introduce a policy-aligned predictive verifier (PAV) that anticipates the consequences of candidate action prefixes and evaluates their compatibility with successful continuation before execution. Rather than using future prediction to generate actions, our method evaluates existing proposals in the VLA's...
| Authors | Minkyu Kim, Junhoo Lee, Seungyeon Kim et al. |
|---|---|
| Primary category | cs.RO |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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