Papers by Gal Lavee

1 papers
Cross-Cultural Transfer Learning for Text Classification (D19-1)

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Challenge: a large dataset is required to achieve competitive performance in most natural language tasks. large datasets are expensive, time consuming, and error-prone.
Approach: They propose a transfer-learning framework that leverages bilingual corpora for natural language text classification using no task-specific data.
Outcome: The proposed framework can achieve good performance on formality classification and sarcasm detection tasks without any task-specific labeled data.

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