Datasets:

FrontierCS
/

Frontier-CS

@@ -2,174 +2,43 @@
 license: apache-2.0
 task_categories:
   - text-generation
-  - question-answering
 language:
   - en
 tags:
   - code
-  - benchmark
-  - evaluation
   - algorithms
-  - systems
-  - machine-learning
-  - security
-  - optimization
 size_categories:
-  - 100K<n<1M
-pretty_name: Frontier-CS
 ---
-<p align="">
-  <a href="https://frontier-cs.org">
-    <img src="assets/logo.png" alt="Frontier-CS Logo" width="2000"/>
-  </a>
-</p>
-<h2 align="center">
-Evolving Challenges for Evolving Intelligence
-</h2>
-<p align="center">
-  <a href="https://frontier-cs.org"><img src="https://img.shields.io/badge/Website-frontier--cs.org-orange?logo=googlechrome" alt="Website"></a>
-  <a href="https://frontier-cs.org/leaderboard"><img src="https://img.shields.io/badge/Leaderboard-View_Rankings-purple?logo=trophy" alt="Leaderboard"></a>
-  <a href="https://discord.gg/k4hd2nU4UE"><img src="https://img.shields.io/badge/Discord-Join_Community-5865F2?logo=discord&logoColor=white" alt="Discord"></a>
-  <a href="https://deepwiki.com/FrontierCS/Frontier-CS"><img src="https://img.shields.io/badge/DeepWiki-Documentation-blue?logo=bookstack&logoColor=white" alt="DeepWiki"></a>
-  <br>
-  <img src="https://img.shields.io/badge/Research_Problems-63-blue" alt="Research Problems">
-  <img src="https://img.shields.io/badge/Algorithmic_Problems-118-green" alt="Algorithmic Problems">
-</p>
-## What is Frontier-CS?
-**Frontier-CS** is an _unsolved_, _open-ended_, _verifiable_, and _diverse_ benchmark for evaluating AI on challenging computer science problems.
-Think of it as an "exam" for AI, but instead of easy textbook questions, we give problems that are genuinely difficult: ones that researchers struggle with, that have no known optimal solutions, or that require deep expertise to even attempt.
-## Why Frontier-CS?
-Current benchmarks are becoming too easy. Models score 90%+ on many existing coding benchmarks, but that doesn't mean they can actually do useful research or solve real-world engineering challenges.
-**Frontier-CS is different:**
-|            | Traditional Benchmarks                     | Frontier-CS                                             |
-| ---------- | ------------------------------------------ | ------------------------------------------------------- |
-| Difficulty | Often saturated with evolving intelligence | _Unsolved_: no solution has achieved perfect scores     |
-| Problems   | Textbook-style, known solutions            | _Open-ended_ research & optimization challenges         |
-| Evaluation | Binary pass-or-fail                        | _Verifiable_ continuous scoring, always room to improve |
-| Scope      | Usually one domain                         | _Diverse_: systems, ML, algorithms, security, and more  |
-**[Leaderboard →](https://frontier-cs.org/leaderboard)** | Browse example problems at [frontier-cs.org](https://frontier-cs.org)
-## Getting Started
-### Installation
-```bash
-git clone https://github.com/FrontierCS/Frontier-CS.git
-cd Frontier-CS
-# Install dependencies (using uv, recommended)
-uv sync
-# Or with pip:
-pip install -e .
-```
-### Try it yourself
-Here's [Algorithmic Problem 0](algorithmic/problems/0/statement.txt) - try to beat GPT-5!
-```bash
-# Start the judge server
-cd algorithmic && docker compose up -d
-# Run the example solution (Human Expert Solution)
-frontier-eval --algorithmic 0 problems/0/examples/reference.cpp
-# Run the example solution (GPT-5 Thinking Solution)
-frontier-eval --algorithmic 0 problems/0/examples/gpt5.cpp
-# Try you own solution!
-frontier-eval --algorithmic 0 <your_solution.cpp>
-```
-<p align="center">
-  <img src="assets/teaser.png" alt="Example Problem" width="800"/>
-</p>
-### Research Problems
-```bash
-# List all problems
-frontier-eval --list
-# Evaluate a generated solution locally for flash_attn problem (requires Docker)
-frontier-eval flash_attn <your_solution.py>
-# Evaluate on cloud (requires SkyPilot)
-frontier-eval flash_attn <your_solution.py> --skypilot
-```
-See [research/README.md](research/README.md) for full documentation.
-### Algorithmic Problems
-```bash
-# Start the judge server
-cd algorithmic && docker compose up -d
-# Evaluate a solution
-frontier-eval --algorithmic 1 <your_solution.cpp>
-```
-#### Raw Score
-Frontier-CS supports unbounded scoring for algorithmic problems, enabling open-ended evaluation compatible with algorithm evolution frameworks such as OpenEvolve.
-```bash
-# Get unbounded score (without clipping to 100)
-frontier-eval --algorithmic --unbounded 1 <your_solution.cpp>
-```
-#### Note
-1. We currently support C++17 only for algorithmic problem solutions.
-2. Reference solutions and hidden tests are withheld; full evaluation and leaderboard inclusion require submission.
-See [algorithmic/README.md](algorithmic/README.md) for full documentation.
-### Python API
 ```python
-from frontier_cs import FrontierCSEvaluator
-evaluator = FrontierCSEvaluator()
-# Evaluate a research problem
-result = evaluator.evaluate("research", problem_id="flash_attn", code=my_code)
-print(f"Score: {result.score}")
-# Evaluate an algorithmic problem
-result = evaluator.evaluate("algorithmic", problem_id=1, code=cpp_code)
-print(f"Score: {result.score}")
-# Get unbounded score for algorithmic problems
-result = evaluator.evaluate("algorithmic", problem_id=1, code=cpp_code, unbounded=True)
-print(f"Score (bounded): {result.score}")
-print(f"Score (unbounded): {result.score_unbounded}")
 ```
-## Submitting Results
-We release partial test cases so you can develop and debug locally. For full evaluation and leaderboard inclusion, submit your solutions to qmang@berkeley.edu, or wenhao.chai@princeton.edu, or zhifei.li@berkeley.edu following the instructions in [SUBMIT.md](SUBMIT.md).
-Questions? Join our [Discord](https://discord.gg/k4hd2nU4UE)
-## Acknowledgments
-Some problems are adapted from [ALE-bench](https://github.com/SakanaAI/ALE-Bench) and [AI-Driven Research for Systems (ADRS)](https://ucbskyadrs.github.io/).
-## Citing Us
-If you use Frontier-CS in your research, please cite:
-```bibtex
-```

 license: apache-2.0
 task_categories:
   - text-generation
 language:
   - en
 tags:
   - code
   - algorithms
+  - competitive-programming
+  - research
 size_categories:
+  - n<1K
 ---
+# Frontier-CS Dataset
+A benchmark dataset for evaluating AI systems on challenging computer science problems.
+## Dataset Description
+This dataset contains 192 problems across two categories:
+- **Algorithmic**: 129 competitive programming problems with automated judging
+- **Research**: 63 open-ended research problems
+## Dataset Structure
+Each problem has the following fields:
+- `problem_id`: Unique identifier for the problem
+- `category`: Either "algorithmic" or "research"
+- `statement`: The problem statement text
+- `config`: YAML configuration for evaluation
+## Usage
 ```python
+from datasets import load_dataset
+dataset = load_dataset("FrontierCS/Frontier-CS")
 ```
+## License
+Apache 2.0