| description | How to write compositional language model programs |
|---|---|
| cover | https://oughtinc.github.io/static/images/primer-cover.jpeg |
| coverY | 0 |
You’ll learn how to:
- Amplify language models like GPT-3 through recursive question-answering and debate
- Reason about long texts by combining search and generation
- Run decompositions quickly by parallelizing language model calls
- Build human-in-the-loop agents
- Use verification of answers and reasoning steps to improve responses
- And more!
Example of a decomposition for reasoning about papers.
The book focuses on techniques that are likely to remain relevant for better language models.
How to cite this book
Please cite this book as:
{% code overflow="wrap" %}
A. Stuhlmüller and J. Reppert and L. Stebbing (2022). Factored Cognition Primer. Retrieved December 6, 2022 from https://primer.ought.org.
{% endcode %}
BibTeX:
@misc{primer2022,
author = {Stuhlmüller, Andreas and Reppert, Justin and Stebbing, Luke},
title = {Factored Cognition Primer},
year = {2022},
howpublished = {\url{https://primer.ought.org}},
urldate = {2022-12-06}
}