Think Only When Needed: Prompt-Authority Control for Selective Slow-Path Intervention in Vision-Language-Action Manipulation

arXiv:2608.23224v1 Announce Type: cross Abstract: Retrieval can efficiently and effectively augment a frozen vision--language--action (VLA) policy without retraining, yet retrieved text becomes a control intervention once it enters the executed prompt. In a matched audit, raw appended text reduces mean success from 92.47% to 3.00%, while meaningful and length-matched meaningless appends both fail on all 500 states. This result identifies prompt-form collapse: changing the instruction form, rather than adding useful semantics, can dominate execution. We introduce TOWN-VLA (Think Only When Needed), a prompt-authority interface that separates candidate generation from permission to alter the policy input. A fixed compatibility rule authorizes a canonical compact instruction; otherwise, the interface restores the original Base prompt exactly. Across 900 audited routes, every route follows this contract: 525 routes recover Base with matching hashes, and all 375 authorized prompts preserve the task signature. On a matched 4imes7 LIBERO-Plus evaluation with 10{,}030 episodes per method, success rises from 69.5% to 73.1% (+362 episodes; 95% CI 1.89--5.45 points), improving on six perturbation axes and all four suites. On a physical PiPER arm with a frozen pizerofive{} checkpoint, success rises from 52.7% to 78.7% over 150 trials per method (p=3.16imes10^{-6}). Prompt authority is enforceable for a frozen controller; oracle-free admission calibration is the next deployment target.

Source: arXiv cs.AI | 2026-08-25