The Verification Gap in Networked Physical AI: A Post-Semantic Communication Framework

2026-08-19

AI Summary

该论文针对网络化物理AI中的验证缺口问题，提出了一种后语义通信框架，通过证据要求、记录验证及最终授权等步骤来解决提案与执行间的不匹配。

Abstract

A task-effective proposal is not yet a justified physical action. In networked Physical AI, a proposal may be understood while valid, timely, proposal-bound evidence or the authority required to finalize an action remains unavailable. We call this mismatch the verification gap and introduce a Post-Semantic Communication Framework for the systems interface between proposal formation and physical execution. The framework begins with application-declared evidence requirements, represents qualifying observations as evidence records, validates supporting and conflicting records through one path, and separates evidence sufficiency from authorized finalization and a downstream runtime gate. It further distinguishes evidence transfer, which can enlarge the record set reachable by a finalizer, from evidence coordination, which can suppress transmission around records already held at the finalization endpoint. Finite-state framework checks verify that the evaluator implements the declared distinctions consistently. Under the declared model, the controlled communication study exposes a finalizer-dependent asymmetry: sender-finalized Feedback uses evidence transfer to expand evidence reachability throughout the feasible plotted region, whereas receiver-finalized Feedback uses coordination to suppress redundant payload until loss, latency, freshness, and deadline costs shift selection to One-way. Finally, an episode-level reporting schema defines common denominators for future measured Physical-AI studies.

Problem

• Verification Gap
• Networked Physical AI
• Post-Semantic Communication Framework

Innovation

• Post-Semantic Communication Framework
• Verification Gap
• Evidence Transfer
• Evidence Coordination