Natural-Language-Processing

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Papers

자연어처리 관련 paper들과 해당 논문 review입니다. (2022년 이전에 작성된 글은 다음 링크에서 확인하실 수 있습니다. [링크])

Date	keywords	Institute	Paper	review	Publication
2023-03			A Survey of Large Language Models	link-1, link-2
2023-02	LLaMA-1	Meta	LLaMA: Open and Efficient Foundation Language Models	link
2023-07	LLaMA-2	Meta	Llama 2: Open Foundation and Fine-Tuned Chat Models	link
2024-04	LLaMA-3	Meta	LLaMA3	link
2024-01	TinyLlama		TinyLlama: An Open-Source Small Language Model	link
2023-05	GQA	Goggle Research	GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints	link	EMNLP 2023
2024-05		Anthropic	Mapping the Mind of a Large Language Model	link
2023-05	TinyStories	Microsoft	TinyStories: How Small Can Language Models Be and Still Speak Coherent English?	link
2023-06	Phi-1	Microsoft	Phi-1: Textbooks Are All You Need	link
2023-09	Phi-1.5	Microsoft	Textbooks Are All You Need II: phi-1.5 technical report	link
2023-12	Phi-2	Microsoft	Phi-2: The surprising power of small language models	link
2024-05	Phi-3	Microsoft	Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone	link
2023-07			Chinchilla’s Death	link
2024-03			RAFT: Adapting Language Model to Domain Specific RAG	link

📒 LLM 시리즈: 기본 개념부터 최신 LLM 까지

• [1] DeepLearning 기본 이론
• [2] Network - CNN, RNN, LSTM, Transformer
• [3-1] A Survey of Large Language Models - 다양한 LLMs부터, Data, Architecture, Training 까지
• [3-2] A Survey of Large Language Models - Adaptation of LLMs
• [4] RAG (Retriever Augumented Generation)