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We propose a simple yet effective approach for improving Korean wordrepresentations using additional linguistic annotation (i.e. Hanja). We employcross-lingual transfer learning in training word representations by leveragingthe fact that Hanja is closely related to Chinese. We evaluate the intrinsicquality of representations learned through our approach using the word analogyand similarity tests. In addition, we demonstrate their effectiveness onseveral downstream tasks, including a novel Korean news headline generationtask.

Don't Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja