---
license: apache-2.0
task_categories:
- other
---

# EqR-data

This repository contains the datasets used in the paper [Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning](https://huggingface.co/papers/2605.21488).

The datasets are designed to evaluate scalable test-time reasoning in iterative latent models, specifically focused on learning task-conditioned attractors.

## Dataset Details

The repository includes data for two main reasoning tasks:
- **Sudoku-Extreme**: A set of challenging Sudoku puzzles designed to test the limits of iterative reasoning models, following the setup from [HRM](https://github.com/sapientinc/HRM).
- **Maze-Unique**: A dataset of 30x30 mazes where each maze has a unique solution path and specific length constraints.

## Links

- **Paper**: [Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning](https://huggingface.co/papers/2605.21488)
- **GitHub**: [locuslab/eqr](https://github.com/locuslab/eqr)
- **Project Page**: [X (Twitter) Thread](https://x.com/huskydogewoof/status/2057641657580064941?s=20)

## Usage

The datasets can be downloaded using the scripts provided in the official GitHub repository:

```bash
git clone https://github.com/locuslab/eqr
cd eqr
bash scripts/download_artifacts.sh
```

## Citation

```bibtex
@article{huang2026equilibrium,
  title={Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning},
  author={Huang, Benhao and Geng, Zhengyang and Kolter, Zico},
  journal={arXiv preprint arXiv:2605.21488},
  year={2026}
}
```