Attention Is All You Need
Paper
•
1706.03762
•
Published
•
44
LLM papers
It is a collection of papers that are useful in studying LLM.
Note Basic
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 30Note Basic
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 48Note Basic understanding of Reinforcement fine-tuning method.
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 36Note Greatness paper to under standing about context and LLM
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Paper • 2005.11401 • Published • 12Note RAG Methodology
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 11Note falsh attention
LIMA: Less Is More for Alignment
Paper • 2305.11206 • Published • 21Note Optional: Think about Data
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
Paper • 2305.14045 • Published • 5Note Optional: Think about Data
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77Note Optional: Think about Data
Deduplicating Training Data Makes Language Models Better
Paper • 2107.06499 • Published • 4Note Optional: Think about Data
Not All Attention Is All You Need
Paper • 2104.04692 • Published • 2Note We have to think about what is really important component about Transformer model.
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 242Note Llama2 paper
Mistral 7B
Paper • 2310.06825 • Published • 47Note Mistral 7B paper
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25Note New metric to evaluate LLM