Papers by Alan Do-Omri

1 papers
Do we need Label Regularization to Fine-tune Pre-trained Language Models? (2023.eacl-main)

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Challenge: Knowledge Distillation (KD) is a label regularization technique that can be replaced with lighter teacher-free variants such as the label-smoothing technique.
Approach: They propose to use knowledge distillation to train student models by deploying the teacher network during training.
Outcome: The proposed method can be replaced with lighter teacher-free variants on PLMs with more than 600 distinct trials and ran each configuration five times.

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