# The Artificial Benchmark for Community Detection with Outliers and Overlapping Communities (ABCD+o2)

arXiv: https://arxiv.org/abs/2506.05486 · HTML: https://mlsanity.com/paper/2506.05486/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jun 2025.

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

- [Multilayer Artificial Benchmark for Community Detection (mABCD)](https://mlsanity.com/paper/2507.10795/) (2025)
- [Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator](https://mlsanity.com/paper/2602.02044/) (2026)
- [A Pragmatic Method for Comparing Clusterings with Overlaps and Outliers](https://mlsanity.com/paper/2602.14855/) (2026)

## Abstract (arXiv)

The Artificial Benchmark for Community Detection (ABCD) graph is a random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs similar to the well-known LFR model but it is faster, more interpretable, and can be investigated analytically. In this paper, we use the underlying ingredients of the ABCD model, and its generalization to include outliers (ABCD+o), and introduce another variant that allows for overlapping communities, ABCD+o2.