SELF-ATTENTION NEURAL NETWORK ARCHITECTURES

Challenge:

Existing methods for story generation struggle with staying coherent for long periods of time.

Approach:

They propose a controlled generation task which expands a sequence of facts into a longer narrative.

Outcome:

The proposed model produces competitive fluency while adhering to the requested facts.

Papers with self-attention neural network architectures