# Explainable Abstract Trains Dataset

arXiv: https://arxiv.org/abs/2012.12115 · HTML: https://mlsanity.com/paper/2012.12115/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Dec 2020.

## Built on by (most cited first, 3 of 3)

- [On Modifying a Neural Network's Perception](https://mlsanity.com/paper/2303.02655/) (2023)
- [On the Performance of Concept Probing: The Influence of the Data (Extended Version)](https://mlsanity.com/paper/2507.18550/) (2025)
- [Concept Probing: Where to Find Human-Defined Concepts (Extended Version)](https://mlsanity.com/paper/2507.18681/) (2025)

## Abstract (arXiv)

The Explainable Abstract Trains Dataset is an image dataset containing simplified representations of trains. It aims to provide a platform for the application and research of algorithms for justification and explanation extraction. The dataset is accompanied by an ontology that conceptualizes and classifies the depicted trains based on their visual characteristics, allowing for a precise understanding of how each train was labeled. Each image in the dataset is annotated with multiple attributes describing the trains' features and with bounding boxes for the train elements.