# Using Causal Threads to Explain Changes in a Dynamic System

arXiv: https://arxiv.org/abs/2311.11334 · HTML: https://mlsanity.com/paper/2311.11334/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 23 references that are in the map.
- First posted on arXiv 19 Nov 2023.

## Builds on (most cited first, 1 of 1)

- [Principles of Explanation in Human-AI Systems](https://mlsanity.com/paper/2102.04972/) (2021)

## Built on by (most cited first, 1 of 1)

- [Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI](https://mlsanity.com/paper/2510.04978/) (2025)

## Abstract (arXiv)

We explore developing rich semantic models of systems. Specifically, we consider structured causal explanations about state changes in those systems. Essentially, we are developing process-based dynamic knowledge graphs. As an example, we construct a model of the causal threads for geological changes proposed by the Snowball Earth theory. Further, we describe an early prototype of a graphical interface to present the explanations. Unlike statistical approaches to summarization and explanation such as Large Language Models (LLMs), our approach of direct representation can be inspected and verified directly.