Papers by Seungwoo Cho

2 papers
Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model (2022.emnlp-main)

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Challenge: Existing methods to train text style transfer models with adversarial loss degrade fluency compared to other metrics.
Approach: They propose a method which leverages a pretrained language model to improve fluency by restructuring the discriminator and the model itself.
Outcome: The proposed model achieves state-of-the-art on three public benchmarks and achieved state-outperformance on the overall metrics.
Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization (2020.coling-main)

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Challenge: Existing methods for text summarization are based on recall-oriented understudy for gisting evaluation (ROUGE) scores do not reflect semantic meaning correspondences between generated and reference summaries.
Approach: They propose to use Korean as a summarization language to generate a shorter form of text from the source document preserving salient information.
Outcome: The proposed evaluation metrics improve the correlation between the metrics and human judgment.

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