Deep Attentive Ranking Networks for Learning to Order Sentences

Understand

We present an attention-based ranking framework for learning to order sentences given a paragraph.

• Our framework is built on a bidirectional sentence encoder and a self-attention based transformer network to obtain an input order invariant representation of paragraphs.
• Moreover, it allows seamless training using a variety of ranking based loss functions, such as pointwise, pairwise, and listwise ranking.
• We apply our framework on two tasks: Sentence Ordering and Order Discrimination.