RPCL, a training-only framework, enhances pair confidence in multimodal emotion-cause pair extraction by enforcing discriminative and stable confidence margins. It outperforms a base model on ECF, MECAD, and MEC4 by 2.58 to 2.83 percentage points in Pair F1 and improves mean Pair AUPRC across datasets, with stronger separation between gold pairs and hard negatives.