Papers by Chihan Huang

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Challenge:	Despite the lack of pre-trained models for ancient Chinese poetry, the unique artistry and structural nuances of Chinese poetry present complex challenges for machine learning in creative applications.
Approach:	They propose a BERT-based model incorporating sentiment and pinyin embeddings into the model, enhancing its sensitivity to emotional information and addressing challenges posed by the phenomenon of multiple pronunciations for the same Chinese character.
Outcome:	The proposed model outperforms existing models on poem generation and sentiment classification tasks and is state-of-the-art in automatic and manual evaluations.