---
license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - code
  - python
  - ai-safety
  - control
  - apps
pretty_name: APPS-cleaned for AI Control replication
size_categories:
  - 1K<n<10K
---

# control-apps-cleaned

A curated subset of the [APPS dataset](https://github.com/hendrycks/apps) (Hendrycks et al., NeurIPS 2021), pre-filtered for use in the ARENA *AI Control* chapter — a teaching replication of Greenblatt et al. 2023 ([arXiv:2312.06942](https://arxiv.org/abs/2312.06942)).

## What's in here

- **`cleaned_apps.jsonl`** — 1,202 problems from the APPS "interview" split, filtered to a uniform I/O schema (inputs and outputs are each one of `list[str]`, `list[int]`, `list[list[str]]`, `list[list[int]]`). Each line is a JSON record with the original APPS fields plus two added fields:
  - `input_type`  — one of `"list of strings"`, `"list of integers"`, `"list of lists of strings"`, `"list of lists of integers"`
  - `output_type` — same vocabulary

The filtering removes problems whose original I/O was strings-with-embedded-newlines (which broke the chapter's `main(input)` function-call interface).

## Why this exists

The original APPS dataset has inputs as raw stdin strings, which doesn't play nicely with the inspect_ai sandbox calling `main(input)` directly. This filtered subset lets every problem be solved by a function `def main(input: list[str]) -> list[str]: ...` without per-problem dispatch on the input shape.

## Usage

```python
from huggingface_hub import hf_hub_download
import json

path = hf_hub_download(
    repo_id="styme3279/control-apps-cleaned",
    filename="cleaned_apps.jsonl",
    repo_type="dataset",
)

with open(path) as f:
    apps = [json.loads(line) for line in f]

print(len(apps), "problems")
print(apps[0].keys())
```

## Provenance

- Upstream source: [hendrycks/apps](https://github.com/hendrycks/apps), interview-difficulty split
- Filter script: `utils.clean_dataset` in the ARENA chapter `chapter3_llm_evals/exercises/part5_ai_control/utils.py`
- Used by: ARENA chapter 3.5 (AI Control)

## License

MIT, inherited from the upstream APPS dataset.