  Natural language inference (NLI) is a central problem in language
understanding. End-to-end artificial neural networks have reached
state-of-the-art performance in NLI field recently.
  In this paper, we propose Character-level Intra Attention Network (CIAN) for
the NLI task. In our model, we use the character-level convolutional network to
replace the standard word embedding layer, and we use the intra attention to
capture the intra-sentence semantics. The proposed CIAN model provides improved
results based on a newly published MNLI corpus.
