BRIDGE reduces bias against high-scoring ELL students in automated scoring by generating synthetic samples via inter-group content pasting and quality discrimination, achieving fairness gains comparable to additional real data.
IEEE Transactions on Learning Technologies15(3), 364–375 (2022)
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GL-LFGNN applies Liang-Kleeman causal information flow within a global-local dual-branch GNN architecture to reach 86.17% arousal and 86.71% valence accuracy on the MEEG dataset using only 37K parameters.
citing papers explorer
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BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation
BRIDGE reduces bias against high-scoring ELL students in automated scoring by generating synthetic samples via inter-group content pasting and quality discrimination, achieving fairness gains comparable to additional real data.
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GL-LFGNN:A Global-Local Dual-branch Causal Graph Neural Network Based on Liang-Kleeman Information Flow for EEG Emotion Recognition
GL-LFGNN applies Liang-Kleeman causal information flow within a global-local dual-branch GNN architecture to reach 86.17% arousal and 86.71% valence accuracy on the MEEG dataset using only 37K parameters.