연세대 인공지능학회 YAI

RoBERTa: A Robustly Optimized BERT Pretraining Approach * YAI 9기 진현빈님이 창의자율과제 NLP팀에서 작성한 글입니다 https://arxiv.org/abs/1907.11692 RoBERTa: A Robustly Optimized BERT Pretraining Approach Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging. Training is computationally expensive, often done on private datasets of differ..

Transformer * YAI 9기 윤수진님이 창의자율과제 NLP팀에서 작성한 글입니다. 논문 소개 Attention Is All You Need Transformer, 고려대학교 산업경영공학과 일반대학원 Unstructured Data Analysis, Youtube The Illustrated Transformer, Jay Alammar, Github Attention Is All You Need The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models a..

분류: NLP 생성일: 2021년 7월 20일 오후 5:41 연도: 2018 저자: Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. 진행 상황: Modifying 키워드: Attention, Bidirectional, Transformer Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805. Overall Summary BERT는 구글이 공개한 NLP 모델로, 언어 표현(language representati..