Character-level Intra Attention Network for Natural Language Inference

Han Yang; Jos\'e A. R. Fonollosa; Marta R. Costa-juss\`a

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arxiv 1707.07469 v1 pith:ZXD34N6C submitted 2017-07-24 cs.CL cs.LG

Character-level Intra Attention Network for Natural Language Inference

Han Yang , Marta R. Costa-juss\`a , Jos\'e A. R. Fonollosa This is my paper

classification cs.CL cs.LG

keywords attentioncharacter-levelintralanguagenetworkcianinferencemodel

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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.

Character-level Intra Attention Network for Natural Language Inference

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