LLM Papers

Deep dives into the papers that built the modern LLM stack — transformers, pretraining, alignment, efficiency, and reasoning.

2026

• Tree of Thoughts: Deliberate Problem Solving 06/21

• AutoGen: Multi-Agent Conversation as Computation 06/14

• Generative Agents: Believable Simulacra of Human Behavior 06/07

• Reflexion: Verbal Reinforcement Learning for Language Agents 05/31

• Toolformer: Language Models That Teach Themselves to Use Tools 05/24

• ReAct: Reasoning + Acting in Language Models 05/17

• RAG: Retrieval-Augmented Generation 05/10

• DeepSeek-R1: Reasoning via Reinforcement Learning 05/03

• Mixtral of Experts: Sparse Mixture of Experts 04/26

• LLaMA: The Open-Weight Catalyst 04/19

• FlashAttention: IO-Aware Exact Attention 04/12

• LoRA: Low-Rank Adaptation of Large Models 04/05

• Chain-of-Thought Prompting: Let the Model Think Step by Step 03/29

• InstructGPT: Aligning LLMs with Human Preference (RLHF) 03/22

• GPT-3 and Few-Shot Learning at Scale 03/15

• BERT: Bidirectional Pretraining from Transformers 03/08

• The Transformer: Attention Is All You Need 03/01