Newest papers

PACT-VLA: Speculative Action-Chunk Verification with Pre-Commit Observations

Yixiang Zhu, Ruilong Wu, Yonghao Chen, Jiaxiang Zou, Yusong Hu, Xinyu Chen · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28019 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

在现实世界的设置中,下一个操作块被生成,而机器人仍在执行前一项任务时,新的操作块和场景都发生了变化,所以在实时观察和任务的成功会随着推断延迟的增长而急剧下降,因此下一个操作块被部署在现实世界的设置中,所以下一个操作块被生成,而机器人仍在执行前一项任务时,机器人和场景发生了变化,因此在执行期间,机器人和场景被条件定位在静止观察和任务的成功会急剧下降。我们的关键见解是,生成多个候选人延迟可以作为决定时间来评估最新观察,但现有的多候选人方法既可以将候选人评估为具有静止推断开始观察的候选人,也可重新使用现有的60%的候

Machine translation (Meta M2M100); the English original follows.

Abstract

Vision-language-action (VLA) policies are commonly deployed with asynchronous inference in real-world settings, where the next action chunk is generated while the robot is still executing the previous one. By the time the new chunk is committed, the robot and scene have changed, so the chunk is conditioned on a stale observation and task success drops sharply as this inference delay grows. Generating multiple candidate chunks could let newer observations inform the final choice, but existing multi-candidate methods either rank candidates with the stale inference-start observation or repeatedly switch between candidates during execution, which can make the executed action sequence discontinuous. Our key insight is that inference delay can be used as decision time. While candidate generation is still underway, candidate selection can reuse the VLA itself to choose the complete action chunk that best fits a later observation. We propose PACT-VLA, a training-free framework that generates candidates from the inference-start observation and selects one using this pre-commit observation. Its scoring function, FlowRes, measures the residual between each candidate's implied flow direction and the velocity predicted by the frozen policy under the pre-commit observation, requiring no separate verifier. A pipelined implementation overlaps observation processing with candidate generation and batches scoring, so selection adds no control-step delay on the evaluated hardware. At a four-step delay, PACT-VLA improves average success by 15.0 percentage points over RTC on Kinetix and by 5.2 points over single-candidate asynchronous execution with GR00T N1.7 on LIBERO, and it further improves existing delay-robust methods. On three real-robot tasks, it raises average success from 60% to 82% over naive asynchronous execution with the same frozen $π_{0.5}$ checkpoint.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Computer science, Asynchronous communication, Task (project management), Inference, Selection (genetic algorithm), Key (lock)

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange