Attention Is All You Need (2017)
Introduced the Transformer architecture, replacing recurrent networks with self-attention and laying the groundwork for all modern LLMs.
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Language Models are Few-Shot Learners (2020)
The GPT-3 paper by OpenAI demonstrated that massive transformers could perform un-fine-tuned tasks effectively via in-context learning.
Training Language Models to Follow Instructions with Human Feedback (2022)
The InstructGPT paper popularised reinforcement learning from human feedback (RLHF) for model alignment.
LoRA: Low-Rank Adaptation of Large Language Models (2021)
Outlined an efficient fine-tuning approach that freezes base weights and injects trainable rank-decomposition matrices.
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