Polaris-Dataset-53K

## Overview Training dataset for Polaris Preview models. The dataset is filtered from [DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset) and [AReal-boba-Data](https://huggingface.co/datasets/inclusionAI/AReaL-boba-Data) ## Format Each row in the `jsonl` file contains: - **problem**: The input problem. - **answer**: The answer to the problem - **difficulty**: The pass rate of the problem estimated by `Deepseek-R1-distill-Qwen-7B` ## Citation ```bibtex @misc{Polaris2025, title = {POLARIS: A Post-Training Recipe for Scaling Reinforcement Learning on Advanced Reasoning Models}, url = {https://hkunlp.github.io/blog/2025/Polaris}, author = {An, Chenxin and Xie, Zhihui and Li, Xiaonan and Li, Lei and Zhang, Jun and Gong, Shansan and Zhong, Ming and Xu, Jingjing and Qiu, Xipeng and Wang, Mingxuan and Kong, Lingpeng} year = {2025} } ```## 概述 本数据集为Polaris Preview模型的训练数据集，从[DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset)与[AReal-boba-Data](https://huggingface.co/datasets/inclusionAI/AReaL-boba-Data)中筛选得到。 ## 数据格式 该`jsonl`文件的每一行均包含以下字段： - **problem（问题）**：输入的待求解问题 - **answer（答案）**：该问题的对应解答 - **difficulty（难度）**：由`Deepseek-R1-distill-Qwen-7B`模型估算得到的该问题的通过率 ## 引用 bibtex @misc{Polaris2025, title = {POLARIS: A Post-Training Recipe for Scaling Reinforcement Learning on Advanced Reasoning Models}, url = {https://hkunlp.github.io/blog/2025/Polaris}, author = {An, Chenxin and Xie, Zhihui and Li, Xiaonan and Li, Lei and Zhang, Jun and Gong, Shansan and Zhong, Ming and Xu, Jingjing and Qiu, Xipeng and Wang, Mingxuan and Kong, Lingpeng} year = {2025} }

搜集汇总

背景与挑战

背景概述

Polaris-Dataset-53K是一个用于训练Polaris预览模型的数据集，由DeepScaleR-Preview-Dataset和AReal-boba-Data经过过滤得到。其数据以jsonl格式存储，每条记录包含问题描述、对应答案以及基于Deepseek-R1-distill-Qwen-7B模型估计的难度等级。