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We explore recently introduced definition modeling technique that providedthe tool for evaluation of different distributed vector representations ofwords through modeling dictionary definitions of words. In this work, we studythe problem of word ambiguities in definition modeling and propose a possiblesolution by employing latent variable modeling and soft attention mechanisms.Our quantitative and qualitative evaluation and analysis of the model showsthat taking into account words ambiguity and polysemy leads to performanceimprovement.

Conditional Generators of Words Definitions