---
title: CPT-Source-OpenMath-33K
canonical_url: "https://www.modelscope.cn/datasets/Tsinghuadhy/CPT-Source-OpenMath-33K"
md_url: "https://www.modelscope.cn/datasets/Tsinghuadhy/CPT-Source-OpenMath-33K.md"
repository: Tsinghuadhy/CPT-Source-OpenMath-33K
chinese_name: "CPT 题源 OpenMath 33K（Pool 3 题源审计后保留）"
last_updated: 2026-05-31
license: MIT
storage_size: "61 MB"
downloads: 48
stars: 1
---

# CPT-Source-OpenMath-33K

> CPT-Source-OpenMath-33K - Tsinghuadhy 在 ModelScope 开源的数据集。CPT-Source-OpenMath-33K

Tsinghuadhy/CPT-Source-OpenMath-33K 是 ModelScope 魔搭社区上的数据集，存储大小 61 MB，采用 MIT 许可。

- **Repository**: Tsinghuadhy/CPT-Source-OpenMath-33K
- **License**: MIT
- **Storage size**: 61 MB
- **Downloads**: 48
- **Stars**: 1
- **Last updated**: 2026-05-31

Source: https://www.modelscope.cn/datasets/Tsinghuadhy/CPT-Source-OpenMath-33K

---

# CPT-Source-OpenMath-33K

Quality-audited subset of [NVIDIA OpenMathReasoning](https://huggingface.co/datasets/nvidia/OpenMathReasoning),
used to build **Pool 3** of the CPT 2× corpus (paper §B.4.1 / Appendix G.2).

The audit uses Qwen3-235B-A22B-Instruct-2507 (`J-OPENMATH-AUDIT`) with
pessimistic 4-sample voting to keep only items whose ground truth is
verifiable and whose statement is unambiguous. Starting from **38,272**
non-MCQ problems, **33,801** are retained (88.3%); the remaining 4,471 are
removed (mainly: GT is descriptive natural language, ambiguous statements,
missing figures, proof-style prompts that leak the target).

The 8K difficulty-balanced **Pool 3** used in CPT 2× is sampled from `kept.jsonl`.

## Files

| File | Lines | Description |
|---|---:|---|
| `kept.jsonl`        | 33,801 | Audited & retained problems (this is what Pool 3 samples from) |
| `removed.jsonl`     |  4,471 | Removed problems with per-rollout audit decisions |
| `audit_stats.json`  |    —   | Per-reason removal breakdown (matches paper Table 40) |

## Schema

```jsonc
{
  "question": "...", "answer": "...",
  "source": "openmath",
  "subject": "aops_c6_high_school_olympiads",
  "difficulty": "easy | medium | hard | very_hard",
  "accuracy": 0.4375,                   // Qwen3-72B-Instruct accuracy (20 rollouts)
  "correct_count": 9, "rollout_num": 20,
  "accuracy_72b_original": 0.6875,
  "filter_results": {
    "final_keep": true,
    "all_keep_decisions": [true, true, true, true],
    "all_categories": ["C","C","C","C"],   // A=remove, B=borderline, C=keep
    "all_confidences": [0.98, 0.95, 0.98, 0.95],
    "all_reasons": ["..."],
    "sampling_method": "pessimistic"
  }
}
```

See [Cognitive Pairwise Training](https://github.com/Tsinghua-dhy/CPT) and
the `J-OPENMATH-AUDIT` prompt in paper Appendix.