Papers by Taesun Whang
Deep Context- and Relation-Aware Learning for Aspect-based Sentiment Analysis (2021.acl-short)
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| Challenge: | Existing methods for aspect-based sentiment analysis (ABSA) consider relationships implicitly among subtasks at the word level. |
| Approach: | They propose a deep contextualized relation-aware network that allows interactive relations among subtasks . they propose self-supervised strategies that deal with multiple aspects . |
| Outcome: | The proposed method outperforms state-of-the-art methods on three widely used benchmarks. |
Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization (2020.coling-main)
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Dongyub Lee, Myeong Cheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, Jaechoon Jo
| 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. |