Par4Sim -- Adaptive Paraphrasing for Text Simplification

COLING 2018 Seid Muhie YimamChris Biemann

Learning from a real-world data stream and continuously updating the model without explicit supervision is a new challenge for NLP applications with machine learning components. In this work, we have developed an adaptive learning system for text simplification, which improves the underlying learning-to-rank model from usage data, i.e. how users have employed the system for the task of simplification... (read more)

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