Re-M3Dr is a multimodal regression framework using adaptive-margin supervised contrastive learning and sharpness-aware gradient modulation to stabilize training and reduce MSE by 29% versus SOTA multimodal methods on clinical eye-imaging datasets for mean deviation prediction.
arXiv preprint arXiv:2502.10816 (2025)
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Re-M3Dr: Rebalanced MultiModal Mean Deviation Regression
Re-M3Dr is a multimodal regression framework using adaptive-margin supervised contrastive learning and sharpness-aware gradient modulation to stabilize training and reduce MSE by 29% versus SOTA multimodal methods on clinical eye-imaging datasets for mean deviation prediction.