Agentic Context Engineering
Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve itself by treating its own context as an evolving
Natural Language Processing
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Chain of Density prompting
Chain of Density (CoD) is a prompting technique for abstractive text summarization with large language models, introduced in the 2023 paper "From Sparse to Dense: GPT-4 Summarization with Chain of Density…
Chain-of-Thought
Chain-of-thought (CoT) is a sequence of intermediate steps that a language model generates before its final answer.
How to Pressure LLMs for Better Output
Pressuring large language models (LLMs) is a family of prompt engineering techniques that try to push a model toward better output by adding emotional weight, urgency, stakes, or coercion to the prompt.
Meta Prompting
Meta prompting (also spelled meta-prompting) is an advanced prompt engineering technique where large language models (LLMs) are used to generate, refine, critique, select, or optimize prompts for themselves or…