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Multi-Layer Random Perturbation Training for improving Model Generalization Efficiently
We propose a simple yet effective Multi-Layer RAndom Perturbation Training algorithm (RAPT) to enhance model robustness and generalization.
Food Development through Co-creation with AI: bread with a "taste of love"
This study explores a new method in food development by utilizing AI including generative AI, aiming to craft products that delight the senses and resonate with consumers' emotions.
OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction
We propose an ensemble model for predicting the lexical complexity of words and multiword expressions (MWEs).
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