Stage-wise audio-visual encoders propagate fused intermediate states across layers, making the formation of later representations depend on the readiness of earlier fusion states. Strong local audio-visual agreement provides useful correspondence evidence, yet a fused state also needs sufficient cross-layer and cross-modal support before it can reliably guide later fusion. This paper studies this issue through propagation-aware representation readiness and formulates premature perceptual commitment as a readiness-deficiency problem, where local plausibility, propagation influence, and support insufficiency jointly appear at an intermediate stage. We propose the Delayed Perceptual Commitment Network (DPC-Net), an encoder-level framework that estimates an observable readiness-deficiency surrogate, localizes the intervention-sensitive bottleneck, and applies support-aware correction with cross-layer and cross-modal evidence. DPC-Net preserves task-specific heads, losses, decoding modules, and evaluation protocols, making it applicable to different audio-visual tasks through encoder-side intervention. Experiments on audio-visual speech separation, audio-visual event localization, and audio-visual speech recognition show consistent improvements across reconstruction, localization, and recognition regimes. Further analyses on component contribution, selection criteria, counterfactual intervention, and readiness trajectories support the effectiveness of readiness-guided bottleneck correction.

翻译：阶段式视听编码器跨层级传播融合后的中间状态，使得后续表示的形成依赖于前期融合状态的就绪程度。强局部视听一致性提供了有用的对应证据，但融合状态在可靠引导后续融合前还需获得充分的跨层级与跨模态支撑。本文通过传播感知的表示就绪性研究该问题，将不成熟感知承诺形式化为就绪性缺失问题——局部似然性、传播影响与支撑不足在中间阶段共同作用。我们提出延迟感知承诺网络（DPC-Net），这是一种编码器级框架，可估计可观测的就绪性缺失替代指标，定位干预敏感瓶颈，并运用跨层级与跨模态证据进行支撑感知校正。DPC-Net保留任务特定头部、损失函数、解码模块及评估协议，通过编码器端干预适用于不同视听任务。在视听语音分离、视听事件定位及视听语音识别实验中的结果表明，该方法在重建、定位及识别范式上均实现一致性改进。进一步对组件贡献、选择标准、反事实干预及就绪性轨迹的分析，验证了就绪性引导瓶颈校正的有效性。