CSBA reduces inter-class gradient interference via branch-specific attention in multi-branch CNNs, raising minority-class F1 from 0.261 to 0.522 on imbalanced damage data and Macro-F1 from 0.595 to 0.655 on CIFAR-10-LT.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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A VR study found that dynamic feedback based on completion time, straightness or peak speed improved average pointing performance but produced small or opposite effects for some users.
citing papers explorer
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Class-Specific Branch Attention for Mitigating Gradient Interference under Class Imbalance
CSBA reduces inter-class gradient interference via branch-specific attention in multi-branch CNNs, raising minority-class F1 from 0.261 to 0.522 on imbalanced damage data and Macro-F1 from 0.595 to 0.655 on CIFAR-10-LT.
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Game Changers: Designing and Measuring Dynamic Feedback To Help Users Self-Regulate in a VR Pointing Game
A VR study found that dynamic feedback based on completion time, straightness or peak speed improved average pointing performance but produced small or opposite effects for some users.