Attention Is All You Need
Paper
• 1706.03762 • Published
• 114
LLM Fundamental papers
Note Transformer
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 19Note GPT-3
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GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Paper • 2305.13245 • Published • 6 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 250 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 89 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 259 -
GPT-4 Technical Report
Paper • 2303.08774 • Published • 7
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 24Note RLHF
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 64Note DPO
Statistical Rejection Sampling Improves Preference Optimization
Paper • 2309.06657 • Published • 15Note Rejection Sampling
RoFormer: Enhanced Transformer with Rotary Position Embedding
Paper • 2104.09864 • Published • 17Note ROPE