# XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems

arXiv: https://arxiv.org/abs/2009.00514 · HTML: https://mlsanity.com/paper/2009.00514/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2020.

## Built on by (most cited first, 7 of 7)

- [Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches](https://mlsanity.com/paper/2403.06026/) (2024)
- [ACE, a generic constraint solver](https://mlsanity.com/paper/2302.05405/) (2023)
- [Proceedings of the 2022 XCSP3 Competition](https://mlsanity.com/paper/2209.00917/) (2022)
- [Proceedings of the 2023 XCSP3 Competition](https://mlsanity.com/paper/2312.05877/) (2023)
- [Adaptive Constraint Propagation: Scaling Structured Inference for Large Language Models via Meta-Reinforcement Learning](https://mlsanity.com/paper/2601.00095/) (2025)
- [Hyperparameter Optimization of Constraint Programming Solvers](https://mlsanity.com/paper/2601.11389/) (2026)
- [PyCSP3-Scheduling: A Scheduling Extension for PyCSP3](https://mlsanity.com/paper/2605.14559/) (2026)

## Abstract (arXiv)

In this document, we introduce XCSP3-core, a subset of XCSP3 that allows us to represent constraint satisfaction/optimization problems. The interest of XCSP3-core is multiple: (i) focusing on the most popular frameworks (CSP and COP) and constraints, (ii) facilitating the parsing process by means of dedicated XCSP3-core parsers written in Java and C++ (using callback functions), (iii) and defining a core format for comparisons (competitions) of constraint solvers.