# Questions of science: chatting with ChatGPT about complex systems

arXiv: https://arxiv.org/abs/2303.16870 · HTML: https://mlsanity.com/paper/2303.16870/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 274 references that are in the map.
- First posted on arXiv 29 Mar 2023.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity](https://mlsanity.com/paper/2101.03961/) (2021)
- [node2vec: Scalable Feature Learning for Networks](https://mlsanity.com/paper/1607.00653/) (2016)
- [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://mlsanity.com/paper/1912.08777/) (2019)
- [Epidemic processes in complex networks](https://mlsanity.com/paper/1408.2701/) (2014)
- [Small vulnerable sets determine large network cascades in power grids](https://mlsanity.com/paper/1804.06432/) (2018)
- [Opinion dynamics in social networks: From models to data](https://mlsanity.com/paper/2201.01322/) (2022)
- [Persistence in Complex Systems](https://mlsanity.com/paper/2205.02082/) (2022)
- [Power laws and Self-Organized Criticality in Theory and Nature](https://mlsanity.com/paper/1310.5527/) (2013)
- [The role of geography in the complex diffusion of innovations](https://mlsanity.com/paper/1804.01349/) (2018)

## Abstract (arXiv)

We present an overview of the complex systems field using ChatGPT as a representation of the community's understanding. ChatGPT has learned language patterns and styles from a large dataset of internet texts, allowing it to provide answers that reflect common opinions, ideas, and language patterns found in the community. Our exploration covers both teaching and learning, and research topics. We recognize the value of ChatGPT as a source for the community's ideas.