metadata
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.
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.
- 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
- GitHub: locuslab/eqr
- Project Page: X (Twitter) Thread
Usage
The datasets can be downloaded using the scripts provided in the official GitHub repository:
git clone https://github.com/locuslab/eqr
cd eqr
bash scripts/download_artifacts.sh
Citation
@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}
}