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SAYRE's innovative approach to synthesizing KIE training data leads to substantial performance gains for on-device models, particularly in challenging extraction scenarios.
Spurious correlations in foundation models can be effectively disentangled using a dual-branch approach, achieving superior bias mitigation with minimal parameter adjustments.
