Dolci-Think-RL
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# Dolci-Think-RL
## Dataset Summary
**Dolci-Think-RL** is a deliberate reasoning RL dataset used for training *Olmo-3-32B-Think* model.
It contains **102,026** high-quality prompts covering:
- Math
- Code
- Precise Instruction Following
- General Chat
This dataset is structurally similar to Dolci-Think-RL-7B but with slightly different mixtures.
---
## Dataset Composition
### **Total Samples:** 102,026
### **Original Dataset Contribution**
| Source Dataset | Count |
|----------------|-------|
| IF Multi-Constraint | 29,847 |
| OMEGA Math ([paper](https://arxiv.org/abs/2506.18880)) | 15,000 |
| AceCoder ([paper](https://arxiv.org/abs/2502.01718)) | 10,107 |
| Multi-Subject RLVR ([paper](https://arxiv.org/abs/2503.23829v1)) | 8,129 |
| Tulu 3 Rewritten ([paper](https://arxiv.org/abs/2411.15124)) | 8,040 |
| AceReason-Math ([paper](https://arxiv.org/abs/2505.16400)) | 6,599 |
| KlearReasoner Code | 6,176 |
| WildChat English ([paper](https://arxiv.org/abs/2405.01470)) | 4,539 |
| ORZ Math ([paper](https://arxiv.org/abs/2503.24290)) | 3,000 |
| SYNTHETIC-2 / PrimeIntellect ([blog](https://www.primeintellect.ai/blog/synthetic-2)) | 3,000 |
| MathSub-30K (KlearReasoner Math) ([paper](https://arxiv.org/abs/2508.07629)) | 2,999 |
| DAPO-Math ([paper](https://arxiv.org/abs/2503.14476)) | 2,584 |
| Llama-Nemotron Post-Training Dataset ([paper](https://arxiv.org/abs/2505.00949)) | 2,006 |
### **Dataset Source Counts (Grouped Mixes)**
| Mix | Count |
|------|-------|
| Math RLVR Mixture | 30,182 |
| IF RLVR Mixture | 29,847 |
| Code RLVR Mixture | 21,289 |
| General RLVR Mixture | 20,708 |
---
## Data Sources & Description
### **Instruction Following**
- IFBench/IFEval-derived multi-constraint tasks
- Normalized and filtered
### **Math Reasoning**
Includes data from:
- OMEGA
- AceReason-Math
- ORZ
- DAPO-Math
- MathSub-30K
Covers algebra, combinatorics, geometry, number theory, proofs, and competition-style problems.
### **Code Reasoning**
Includes:
- AceCoder
- KlearReasoner-Code
- SYNTHETIC-2 (PrimeIntellect)
- Llama-Nemotron Post-Training Dataset
All validated using execution-based filtering.
### **General Long-Form Reasoning**
- Multi-Subject RLVR
- Tulu 3 rewritten (filtered via F1 score)
- WildChat English (topic + character filtering)
---
## Processing & Filtering
- **Keyword & topic filtering**
- **Execution-based test-case validation**
- **F1-score filtering** of rewritten prompts
- **Nemotron difficulty-tier selection**
- **Safety filtering + deduplication**
- **Constraint normalization** for IF tasks
---
## License
This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with [Ai2's Responsible Use Guidelines](https://allenai.org/responsible-use).
## Citation
A technical manuscript is forthcoming!
# Dolci-Think-RL
## 数据集概述
**Dolci-Think-RL** 是一款用于训练*Olmo-3-32B-Think*模型的刻意推理强化学习(Reinforcement Learning, RL)数据集。它包含**102,026条**高质量提示词,涵盖以下领域:
- 数学
- 代码
- 精准指令遵循
- 通用对话
该数据集在结构上与Dolci-Think-RL-7B相似,但混合比例略有差异。
---
## 数据集构成
### **总样本数:102,026**
### **原始数据集贡献**
| 源数据集 | 样本量 |
|----------------|-------|
| 多约束指令遵循(IF Multi-Constraint) | 29,847 |
| OMEGA 数学数据集([论文](https://arxiv.org/abs/2506.18880)) | 15,000 |
| AceCoder([论文](https://arxiv.org/abs/2502.01718)) | 10,107 |
| 多学科RLVR(Multi-Subject RLVR,[论文](https://arxiv.org/abs/2503.23829v1)) | 8,129 |
| 重写版Tulu 3([论文](https://arxiv.org/abs/2411.15124)) | 8,040 |
| AceReason-Math([论文](https://arxiv.org/abs/2505.16400)) | 6,599 |
| KlearReasoner 代码数据集 | 6,176 |
| 英文WildChat([论文](https://arxiv.org/abs/2405.01470)) | 4,539 |
| ORZ 数学数据集([论文](https://arxiv.org/abs/2503.24290)) | 3,000 |
| SYNTHETIC-2 / PrimeIntellect([博客](https://www.primeintellect.ai/blog/synthetic-2)) | 3,000 |
| MathSub-30K(KlearReasoner 数学数据集,[论文](https://arxiv.org/abs/2508.07629)) | 2,999 |
| DAPO-Math([论文](https://arxiv.org/abs/2503.14476)) | 2,584 |
| Llama-Nemotron 后训练数据集([论文](https://arxiv.org/abs/2505.00949)) | 2,006 |
### **分组混合数据集来源统计**
| 混合组 | 样本量 |
|------|-------|
| 数学RLVR混合组 | 30,182 |
| 指令遵循RLVR混合组 | 29,847 |
| 代码RLVR混合组 | 21,289 |
| 通用RLVR混合组 | 20,708 |
---
## 数据来源与说明
### **指令遵循任务**
- 源自IFBench/IFEval的多约束任务
- 已完成归一化与过滤处理
### **数学推理任务**
包含以下来源的数据:
- OMEGA
- AceReason-Math
- ORZ
- DAPO-Math
- MathSub-30K
涵盖代数、组合数学、几何学、数论、形式化证明以及竞赛类题型。
### **代码推理任务**
包含以下来源的数据:
- AceCoder
- KlearReasoner-Code
- SYNTHETIC-2(PrimeIntellect)
- Llama-Nemotron 后训练数据集
所有数据均通过执行验证的方式完成过滤。
### **通用长文本推理任务**
- 多学科RLVR
- 重写版Tulu 3(通过F1分数完成过滤)
- 英文WildChat(通过主题与角色特征完成过滤)
---
## 处理与过滤流程
- **关键词与主题过滤**
- **基于执行的测试用例验证**
- **重写提示词的F1分数过滤**
- **Nemotron难度层级筛选**
- **安全过滤与去重**
- **指令遵循任务的约束归一化**
---
## 许可协议
本数据集采用ODC-BY许可协议发布,旨在遵循[AllenAI负责任使用指南](https://allenai.org/responsible-use)用于研究与教育用途。
## 引用信息
相关技术手稿即将发布!
提供机构:
maas
创建时间:
2025-11-21



