Learning to Embed Sentences Using Attentive Recursive Trees

Understand

Sentence embedding is an effective feature representation for most deep learning-based NLP tasks.

• One prevailing line of methods is using recursive latent tree-structured networks to embed sentences with task-specific structures.
• However, existing models have no explicit mechanism to emphasize task-informative words in the tree structure.
• To this end, we propose an Attentive Recursive Tree model (AR-Tree), where the words are dynamically located according to their importance in the task.