This paper proposes a modularized sense induction and representation learning model that jointly learns bilingual sense embeddings that align well in the vector space, where the crosslingual signal in the English-Chinese parallel corpus is exploited to capture the collocation and distributed characteristics in the language pair.
every bilingual sense induction module will experience the degradation during the training process presented in Algorithm 1.