Repository of all NLP-related things(implement, papers...etc)
NLP와 관련된 아키텍처, 논문 등을 정리한 레포입니다.
깃허브 마크다운 LaTex 렌더링 이슈로 인헤, 각 설명 문서 당 .pdf와 markdown 두 개의 버전으로 올렸습니다.
또한, 아래의 링크에서도 확인해보실 수 있습니다.
directory 이름을 클릭하시면 해당 directory로 바로 이동할 수 있습니다.
각 구성 요소들의 링크는 동일 내용을 업로드한 저의 티스토리 페이지로 이동하는 링크입니다.
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각종 논문들을 읽고 리뷰한 내용들을 모아놓은 directory입니다.
- Adam: A Method for Stochastic Optimization (Only Implement)
- Attention is all you need
- BERT: Pre training of Deep Bidirectional Transformers for Language Understanding
- Big Bird: Transformers for Longer Sequences
- Dense Passage Retrieval for Open-Domain Question Answering
- Direct Fact Retrieval from Knowledge Graphs without Entity Linking
- Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
- Effective Approaches to Attention based Neural Machine Translation
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
- FEVER- a large-scale dataset for Fact Extraction and VERification
- Finetuned Language Models Are Zero-Shot Learners
- Generation-Augmented Retrieval for Open-Domain Question Answering
- GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
- Improving Language Understanding by Generative Pre Training
- Language Models are Unsupervised Multitask Learners
- Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
- Mixed Precision Training
- Multilingual Language Processing From Bytes
- Multitask Prompted Training Enables Zero-Shot Task Generalization
- Neural Machine Translation by Jointly Learning to Align and Translate
- Query Expansion by Prompting Large Language Models
- REALM: Retrieval-Augmented Language Model Pre-Training
- REPLUG: Retrieval-Augmented Black-Box Language Models
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
- RoBERTa: A Robustly Optimized BERT Pretraining Approach
- Self-Attention with Relative Position Representations
- The Natural Language Decathlon- Multitask Learning as Question Answering
- Training language models to follow instructions with human feedback
- Using the Output Embedding to Improve Language Models
- RNN
RNN(Recurrent Neural Network)에 대한 설명을 정리해놓은 곳입니다.
- seq2seq
시퀀스-투-시퀀스(Sequence-to-Sequence, seq2seq)에 대한 설명과 구현을 정리해놓은 곳입니다.
see paper NLP_paper map in here
wiil be updated soon