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---
dataset_info:
- config_name: v1_2024
  features:
  - name: id
    dtype: int64
  - name: description
    dtype: string
  - name: time_limit
    dtype: int64
  - name: memory_limit
    dtype: int64
  - name: checker
    dtype: string
  - name: test_cases
    list:
    - name: input
      dtype: string
    - name: output
      dtype: string
  - name: year
    dtype: int64
  - name: date
    dtype: string
  - name: difficulty
    dtype: string
  - name: contest_category
    dtype: string
  - name: contest_name
    dtype: string
  splits:
  - name: test
    num_bytes: 20187500547
    num_examples: 400
  download_size: 12737762718
  dataset_size: 20187500547
- config_name: v1_2025
  features:
  - name: id
    dtype: int64
  - name: description
    dtype: string
  - name: time_limit
    dtype: int64
  - name: memory_limit
    dtype: int64
  - name: checker
    dtype: string
  - name: year
    dtype: int64
  - name: date
    dtype: string
  - name: difficulty
    dtype: string
  - name: contest_category
    dtype: string
  - name: contest_name
    dtype: string
  splits:
  - name: test
    num_bytes: 201028
    num_examples: 56
  download_size: 104645
  dataset_size: 201028
configs:
- config_name: v1_2024
  data_files:
  - split: test
    path: v1_2024/test-*
- config_name: v1_2025
  data_files:
  - split: test
    path: v1_2025/test-*
---
<div align="center">
  <h1>AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions</h1>
</div>

<div align="center" style="line-height: 1;">
  <a href="https://arxiv.org/" target="_blank" style="margin: 2px;">
    <img alt="Comming Soon" src="https://img.shields.io/badge/arXiv-Comming%20Soon-red?logo=arxiv&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
  </a>
  <a href="https://huggingface.co/datasets/m-a-p" target="_blank" style="margin: 2px;">
    <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-m--a--p-536af5" style="display: inline-block; vertical-align: middle;"/>
  </a>
  <a href="https://huggingface.co/datasets/m-a-p/AetherCode/blob/main/LICENSE" style="margin: 2px;">
    <img alt="Dataset License" src="https://img.shields.io/badge/Dataset_License-CC--BY--4.0-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
  </a>
</div>

## Introduction

Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on existing benchmarks, we argue that current evaluations overstate model proficiency, masking a substantial gap between LLMs and elite human programmers. This gap arises from two key limitations: insufficient difficulty and scope of benchmark problems, and evaluation bias from low-quality test cases. To address these shortcomings, we present AetherCode, a new benchmark that draws problems from premier programming competitions such as IOI and ICPC, offering broader coverage and higher difficulty. AetherCode further incorporates comprehensive, expert-validated test suites built through a hybrid of automated generation and human curation, ensuring rigorous and reliable assessment. By combining challenging problem design with robust evaluation, AetherCode provides a more faithful measure of LLM capabilities and sets a new standard for future research in code reasoning.

## Highlights

**Problem Curation from Top-Tier Competitions**: AetherCode is the first benchmark to systematically collect problems from premier programming competitions worldwide, including the Olympiad in Informatics (OI) and the International Collegiate Programming Contest (ICPC). Our process involved a comprehensive collection, meticulous cleaning, and format conversion of problems from PDF to a Markdown+LaTeX structure. Each problem statement was manually proofread for correctness, and a team of competitive programming experts mannotated each problem with classification tags.

**High-Quality Test Case Generation**: We developed a hybrid methodology, combining automated generation with expert annotation, to create high-quality test cases for every problem. We evaluated the correctness and comprehensiveness of our test cases by validating them against a large corpus of collected solutions, enforcing a standard of zero false positives and zero false negatives.

## Quickstart

```python
from datasets import load_dataset

# Login using e.g. `huggingface-cli login` to access this dataset
ds = load_dataset("m-a-p/AetherCode", "v1_2024")
```

## License

This project is licensed under CC-BY-4.0. See the [LICENSE file](https://huggingface.co/datasets/m-a-p/AetherCode/blob/main/LICENSE) for details.