PaperNova
Large Language Models
2022
BEGINNER

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, et al. · 2022

Chain-of-Thought. A few worked-example prompts dramatically improve LLM reasoning on arithmetic, commonsense and symbolic tasks — zero training required.

Start guided workbook →Read original paperPDF

What you'll get

  • Outline: a plain-English breakdown of the paper's core idea, prerequisites, and the concepts you'll need to implement it.
  • Exercises: five to ten hands-on tasks, each with a concept card, a prompt, a starter code stub, and a collapsible reference solution.
  • Runnable notebook: a single .ipynb you can download and open in Jupyter or VS Code to work through every exercise.
  • Extensions: suggested follow-up experiments so you don't stop at a faithful reimplementation.