A lack of labeled corpora obstructs the research progress on implicit discourse relation recognition(DRR)for Chinese,while there are some available discourse corpora in other languages,such as English.In this paper,we propose a cross-lingual implicit DRR framework that exploits an available English corpus for the Chinese DRR task.We use machine translation to generate Chinese instances from a labeled English discourse corpus.In this way,each instance has two independent views: Chinese and English views.Then we train two classifiers in Chinese and English in a co-training way,which exploits unlabeled Chinese data to implement better implicit DRR for Chinese.Experimental results demonstrate the effectiveness of our method.