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

Prepared for *Learning to Steer, Steering to See*. validation is the full local LiveCodeBench v5 export (880 problems), not the 100-row smoke subset. The original converter caps tests at 30 and their combined bytes; this is an execution-budget variant, not unrestricted official LCB evaluation.

| Split | Rows |
| --- | ---: |
| train | 25,276 |
| validation | 880 |
| eurus_validation | 1,024 |

## 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/PRIME-RL/Eurus-2-RL-Data
- https://huggingface.co/datasets/livecodebench/code_generation_lite

## 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-Code", "train", split="train")
validation = load_dataset("caiyuchen/OPV-Code", "validation", split="validation")
```

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