Generative semantic communication uses receiver-side generative priors to reconstruct visual content from compact semantics, making it attractive for bandwidth-limited multimedia delivery. For video, reliable recovery remains difficult because errors accumulate over time, useful evidence is temporally correlated, and the receiver must make decisions under limited interaction, retransmission, and reconstruction budgets. Existing generative semantic communication studies mainly emphasize representation, compression, or generative reconstruction, while recent error-resilient and semantic-HARQ methods still largely operate on encoder-defined or frame-block retransmission units. This paper studies receiver-driven semantic HARQ for generative video reconstruction under a budget-constrained AoIS-AUC objective and argues that the retransmission primitive is itself an important system design variable. We propose tube-structured package-native requests, in which temporally local packages are the channel-visible HARQ objects and are transmitted, dropped, received, and committed at package granularity. Under a controlled comparison protocol with matched backbone, budgets, and channel model, this primitive yields lower time-weighted recovery cost than competitive block-based baselines in practically relevant moderate-to-harsh regimes, while the gap naturally shrinks in near-clean channels. The gain mainly appears as earlier stabilization of the recovery trajectory, while final-quality endpoints remain broadly comparable, and it persists even against a tube-aware block-ranking baseline.

翻译：生成式语义通信利用接收端生成先验从紧凑语义中重建视觉内容，使其在带宽受限的多媒体传输中具有吸引力。对于视频而言，由于误差随时间累积、有效证据存在时间相关性，且接收端需在有限的交互、重传和重建预算下做出决策，可靠恢复仍然困难。现有生成式语义通信研究主要关注表示、压缩或生成式重建，而近期抗差错和语义HARQ方法仍大多基于编码器定义的或帧-块重传单元运作。本文研究在预算约束的AoIS-AUC目标下，面向生成式视频重建的接收端驱动语义HARQ，并提出重传原语本身是重要的系统设计变量。我们提出管状结构的数据包原生请求，其中时间局部数据包是信道可见的HARQ对象，并以数据包粒度进行传输、丢弃、接收和提交。在具有匹配骨干网络、预算和信道模型的受控比较协议下，该原语在中等至恶劣的实际相关信道条件下，相比竞争性的基于块的基线方法实现了更低的时间加权恢复代价，同时在近乎干净的信道中差距自然缩小。增益主要表现为恢复轨迹的早期稳定化，而最终质量终点总体可比，并且即使面对考虑了管状结构的块排序基线，该增益依然存在。