Papers by Hélène De Ribaupierre

1 papers
Go Simple and Pre-Train on Domain-Specific Corpora: On the Role of Training Data for Text Classification (2020.coling-main)

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Challenge: Pre-trained language models provide the foundations for state-of-the-art performance across a wide range of natural language processing tasks, including text classification.
Approach: They compare the performance of a linear classifier based on word embeddings with a pre-trained language model, i.e., BERT, across a wide range of datasets and classification tasks.
Outcome: The proposed method outperforms baselines in standard datasets with large training sets, but in settings with small training datasets it performs better.

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