论文

RAG (Retrieval Augmented Generation)

• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
• Lost in the Middle: How Language Models Use Long Contexts
• Reflexion: Language Agents with Verbal Reinforcement Learning
• Improving language models by retrieving from trillions of tokens
• Generative Agents: Interactive Simulacra of Human Behavior