BERT (2018) 논문 노트
BERT 논문의 핵심 아이디어인 양방향 Transformer encoder, masked language model, next sentence prediction, fine-tuning 패러다임을 정리한 논문 노트.
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LLM 구조 기초: Encoder-only와 Decoder-only
BERT와 GPT 계열을 구분하는 encoder-only, decoder-only 구조를 비교합니다.
LLM 기초: RNN과 순차 처리
Transformer 이전의 대표 구조인 RNN이 문장을 순서대로 처리하는 방식과 한계를 설명합니다.