pal
temporal-graph-gen
pal | temporal-graph-gen | |
---|---|---|
4 | 3 | |
436 | 15 | |
1.4% | - | |
3.1 | 0.0 | |
10 months ago | almost 3 years ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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pal
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Prompt Engineering Guide: Guides, papers, and resources for prompt engineering
Using the terminology that I'm working with this is an example of a second-order analytic augmentation!
Here's another approach of second-order analytic augmentation, PAL: https://reasonwithpal.com
And third-order, Toolformer: https://arxiv.org/abs/2302.04761
The difference isn't in what is going on but rather with framing the approach within the analytic-synthetic distinction developed by Kant and the analytic philosophers who were influenced by his work. There's a dash of functional programming thrown in for good measure!
I have scribbled on a print-out of the article on my desk:
Nth Order
- [R] Faithful Chain-of-Thought Reasoning
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GPT-3: Techniques to improve reliability
GitHub: https://github.com/reasoning-machines/pal
tl;dr -- LLMs are bad at basic arithmetic and logic (as their opening examples with math word problems show), but they do much better if instead of asking them for the answer, you ask for code to compute the answer. Then evaluate or run the code to get the answer.
temporal-graph-gen
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GraphGPT: Extrapolating knowledge graphs from unstructured text
It has been possible to generate impressive graphs from text since GPT-2. Though you need a few tricks to make it work.
Here's an example (my work): https://aclanthology.org/2021.naacl-main.67.pdf
TLDR of the input/output: https://madaan.github.io/res/tldr/graph_gen_tldr.jpg
- [D] Autoregressive model for graph generation?
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Online Text to Diagram Tools
On a related note, I did some work on generating temporal graphs from text: https://arxiv.org/pdf/2010.10077.pdf
Code/models: https://github.com/madaan/temporal-graph-gen
What are some alternatives?
openai-cookbook - Examples and guides for using the OpenAI API
GraphGPT - Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️♂️
qagnn - [NAACL 2021] QAGNN: Question Answering using Language Models and Knowledge Graphs 🤖
spark-joy - ✨😂 2000+ ways to add design flair, user delight, and whimsy to your product.
memprompt - A method to fix GPT-3 after deployment with user feedback, without re-training.
Graphormer - Graphormer is a general-purpose deep learning backbone for molecular modeling.
prompt-lib - A set of utilities for running few-shot prompting experiments on large-language models
dagre-svg
empirical-philosophy - A collection of empirical experiments using large language models and other neural network architectures to test the usefulness of metaphysical constructs.
self-refine - LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Prompt-Engineering-Guide - 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
KeenWrite - Free, open-source, cross-platform desktop Markdown text editor with live preview, string interpolation, and math.