---
dataset_info:
  features:
  - name: index
    dtype: int64
  - name: target
    dtype: int64
  - name: available_numbers
    sequence: int64
  - name: solutions
    sequence: string
  splits:
  - name: train
    num_bytes: 4524413
    num_examples: 22500
  - name: test
    num_bytes: 86631
    num_examples: 400
  download_size: 1757059
  dataset_size: 4611044
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---


# Multi-Solution Countdown Dataset

This dataset is from the paper [The Era of Agentic Organization: Learning to Organize with Language Models](https://arxiv.org/abs/2510.26658).

## Dataset Description

The Multi-Solution Countdown dataset contains mathematical reasoning problems where the goal is to reach a target number using a set of available numbers and basic arithmetic operations (+, -, *, /). Each problem has multiple valid solutions.

## Dataset Structure

| Split | Examples |
|-------|----------|
| Train | 22,500   |
| Test  | 400      |

### Features

- `index`: Integer identifier
- `target`: Target number to reach
- `available_numbers`: List of numbers that can be used
- `solutions`: List of valid mathematical expressions

### Example

```json
{
  "index": 1,
  "target": 655,
  "available_numbers": [8, 9, 26, 43, 47, 60, 68, 69, 70, 78, 82, 87],
  "solutions": ["((26-78)+((68+87)+(8*69)))", "(69-(70-(8*82)))", "(43+(68*9))", "((47+68)+(60*9))"]
}
```

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("CZWin32768/multi-solution-countdown")
```

## Citation

```bibtex
@article{chi2025asyncthink,
  title={The Era of Agentic Organization: Learning to Organize with Language Models},
  author={Chi, Zewen and Dong, Li and Dong, Qingxiu and Hao, Yaru and Wu, Xun and Huang, Shaohan and Wei, Furu},
  journal={arXiv preprint arXiv:2510.26658},
  year={2025}
}
```