File size: 4,028 Bytes
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dataset_info:
features:
- name: problem
dtype: string
- name: solution
dtype: string
- name: candidates
sequence: string
- name: tags
sequence: string
- name: metadata
struct:
- name: answer_score
dtype: int64
- name: boxed
dtype: bool
- name: end_of_proof
dtype: bool
- name: n_reply
dtype: int64
- name: path
dtype: string
splits:
- name: train
num_bytes: 298608789
num_examples: 80661
download_size: 140630996
dataset_size: 298608789
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# AoPS: Art of Problem Solving Competition Mathematics
## Dataset Description
This dataset is a collection of **80,661** competition mathematics problems and solutions obtained from the [Art of Problem Solving (AoPS)](https://artofproblemsolving.com/) community wiki and forums. It covers a wide range of mathematical contests and olympiads, including problems from events such as AIME, BAMO, IMO, and various national and memorial competitions.
The dataset was curated by [AI-MO (Project Numina)](https://huggingface.co/AI-MO), an initiative focused on building AI systems capable of mathematical reasoning at the olympiad level.
## Dataset Structure
### Fields
| Column | Type | Description |
|---|---|---|
| `problem` | `string` | The mathematical problem statement, typically formatted in LaTeX. |
| `solution` | `string` | A solution or proof for the problem. May be empty for some entries. |
| `candidates` | `list[string]` | Alternative or candidate solutions contributed by the community. |
| `tags` | `list[string]` | Metadata tags indicating the origin, contest name, and year (e.g., `"origin:aops"`, `"2022 AIME Problems"`). |
| `metadata` | `dict` | Additional metadata about the problem (see below). |
### Metadata Fields
| Field | Type | Description |
|---|---|---|
| `answer_score` | `int64` | Community score or rating of the answer. |
| `boxed` | `bool` | Whether the answer contains a boxed final result (e.g., `\boxed{42}`). |
| `end_of_proof` | `bool` | Whether the solution includes a complete proof ending. |
| `n_reply` | `int64` | Number of community replies or comments on the problem thread. |
| `path` | `string` | Source path in the AoPS collection (e.g., `Contest Collections/2022 Contests/...`). |
### Splits
| Split | Examples |
|---|---|
| `train` | 80,661 |
## Example
```python
{
"problem": "Let $ABC$ be an acute triangle with altitude $AD$ ($D \\in BC$). The line through $C$ parallel to $AB$ meets the perpendicular bisector of $AD$ at $G$. Show that $AC = BC$ if and only if $\\angle AGC = 90°$.",
"solution": "...",
"candidates": ["..."],
"tags": ["origin:aops", "2022 Contests", "2022 3rd Memorial \"Aleksandar Blazhevski-Cane\""],
"metadata": {
"answer_score": 130,
"boxed": false,
"end_of_proof": true,
"n_reply": 3,
"path": "Contest Collections/2022 Contests/2022 3rd Memorial .../2759376.json"
}
}
```
## Topic Coverage
Problems span a broad range of competition mathematics topics, including:
- **Geometry** -- triangle properties, cyclic quadrilaterals, angle chasing
- **Number Theory** -- divisibility, modular arithmetic, Diophantine equations
- **Algebra** -- inequalities, polynomials, functional equations
- **Combinatorics** -- counting, graph theory, board coloring problems
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("AI-MO/aops")
# Access a problem
print(dataset["train"][0]["problem"])
print(dataset["train"][0]["solution"])
```
## Intended Use
- Training and evaluating mathematical reasoning models
- Benchmarking LLMs on competition-level mathematics
- Studying solution quality and problem difficulty distributions
- Building retrieval-augmented generation (RAG) systems for math tutoring
## Source
All problems and solutions originate from the [Art of Problem Solving](https://artofproblemsolving.com/) community.
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