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Recently,Chinese implicit discourse relation recognition has attracted more and more attention,since it is crucial to understand the Chinese discourse text.In this paper,we propose a novel memory augmented attention model which represents the arguments using an attention-based neural network and preserves the crucial information with an external memory network which captures each discourse relation clustering structure to support the relation inference.Exten-sive experiments demonstrate that our proposed model can achieve the new state-of-the-art results on Chinese Discourse Treebank.We further leverage network visualization to show why our attention and memory model are effective.