Intermediate · NLP
Chain-of-thought prompting
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. An advanced prompting technique that guides LLMs to break down complex problems into intermediate reasoning steps before providing a final answer.
Technical Definition
An advanced prompting technique that guides LLMs to break down complex problems into intermediate reasoning steps before providing a final answer.
How it works
Chain-of-thought prompting is a method to improve the reasoning capabilities of large language models. Instead of asking for a direct answer, the prompt encourages the model to explain its thought process step-by-step, much like a human would. This sequential reasoning helps the LLM arrive at more accurate and well-justified conclusions, especially for complex tasks.
Related Concepts
- Large Language Model (LLM) — A massive neural network trained on vast text corpora to understand and generate human language with remarkable fluency.
- Prompt Engineering — The art of crafting effective input instructions to guide LLM behavior without changing model weights.
- Reasoning — An AI system's ability to draw logical, multi-step conclusions from given information.