CEDO, a combination of modality-specific learning rates, Pareto gradient synergy, and loss rescaling, reports improved accuracy on five Med-VQA benchmarks including two new biased splits.
Loss re-scaling vqa: Re- visiting the language prior problem from a class-imbalance view.IEEE Transactions on Image Processing (TIP), 31:227–238,
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Cause-Effect Driven Optimization for Robust Medical Visual Question Answering with Language Biases
CEDO, a combination of modality-specific learning rates, Pareto gradient synergy, and loss rescaling, reports improved accuracy on five Med-VQA benchmarks including two new biased splits.