Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention

Understand

In this paper, we proposed a sentence encoding-based model for recognizing text entailment.

• In our approach, the encoding of sentence is a two-stage process.
• Firstly, average pooling was used over word-level bidirectional LSTM (biLSTM) to generate a first-stage sentence representation.
• Secondly, attention mechanism was employed to replace average pooling on the same sentence for better representations.