한국어 문서 요약 모델의 성능 향상을 위한 포스트 트레이닝 기법 = Post-training Methods for Improving Korean Document Summarization Model

다국어 초록 (Multilingual Abstract)

The document summarization task generates a short summary based on a long document.
Recently, a method using a pre-trained model based on a transformer model showed high performance.
However, as it was proved that fine-tuning does not train the model optimally due to the learning gap between pre-training and fine-tuning, post-training, which is additional training between pre-training and fine-tuning, was proposed. This paper proposed two post-training methods for Korean document summarization. One was Korean Spacing, which is for learning Korean structure, and the other was First Sentence Masking, which is for learning about document summarization. Experiments proved that the proposed post-training methods were effective as performance improved when the proposed post-training was used compared to when it was not.