---
language:
- en
task_categories:
- text-generation
tags:
- reinforcement-learning
- verl
- opv
configs:
- config_name: train
  data_files:
  - split: train
    path: train.parquet
- config_name: teacher_train
  data_files:
  - split: teacher_train
    path: teacher_train.parquet
- config_name: validation
  data_files:
  - split: validation
    path: validation.parquet
- config_name: aime2025
  data_files:
  - split: aime2025
    path: aime2025.parquet
---
# OPV Math: original experiment data

Prepared for *Learning to Steer, Steering to See*. train is filtered DeepMath (distillation); teacher_train is the original DAPO teacher corpus. validation is AIME2024. These corpora are not interchangeable.

| Split | Rows |
| --- | ---: |
| train | 57,046 |
| teacher_train | 14,116 |
| validation | 30 |
| aime2025 | 30 |

## Provenance and terms

The data is derived from the following sources; their original terms and attribution obligations continue to apply. No new blanket license is asserted over the collection. Source-file and uploaded-file hashes are in `manifest.json`.

- https://huggingface.co/datasets/DeepMath-Team/DeepMath-103K
- https://huggingface.co/datasets/BytedTsinghua-SIA/DAPO-Math-17k
- https://huggingface.co/datasets/HuggingFaceH4/aime_2024

## Format and evaluation

These are byte-for-byte copies of the original Parquet files. All columns, Arrow schemas, nested verifier metadata, row order, prompts and answers are unchanged. Use the existing verl reward functions directly. Each file has a separate Hub configuration because original train/evaluation schemas differ.

Use the full evaluation split and four independently sampled responses per prompt; report **mean@4**, not pass@4. No training responses or model weights are included. Exact normalized-chat train/evaluation overlap: **0 prompts**. Original splits are preserved, including any disclosed overlap, to match existing teacher provenance. This is not a semantic contamination audit.

```python
from datasets import load_dataset
train = load_dataset("caiyuchen/OPV-Math", "train", split="train")
validation = load_dataset("caiyuchen/OPV-Math", "validation", split="validation")
```

The available artifacts differ from several manuscript descriptions. The accompanying repository records these differences instead of relabeling datasets or inventing results.