--- title: Superior-Reasoning-SFT-gpt-oss-120b-Logprob canonical_url: "https://www.modelscope.cn/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob" md_url: "https://www.modelscope.cn/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob.md" repository: Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob last_updated: 2026-01-15 license: cc-by-4.0 storage_size: "47 GB" downloads: 2946 stars: 2 --- # Superior-Reasoning-SFT-gpt-oss-120b-Logprob > Superior-Reasoning-SFT-gpt-oss-120b-Logprob - Alibaba-Apsara 在 ModelScope 开源的数据集。Superior-Reasoning-SFT-gpt-oss-120b-Logprob Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob 是 ModelScope 魔搭社区上的数据集，存储大小 47 GB，采用 cc-by-4.0 许可。 - **Repository**: Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob - **License**: cc-by-4.0 - **Storage size**: 47 GB - **Downloads**: 2946 - **Stars**: 2 - **Last updated**: 2026-01-15 Source: https://www.modelscope.cn/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob --- # Superior-Reasoning-SFT-gpt-oss-120b-Logprob Ali [![GitHub](https://img.shields.io/badge/GitHub-DASD--Thinking-181717?logo=github&logoColor=white)](https://github.com/D2I-ai/dasd-thinking)  [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Checkpoint-DASD--4B--Thinking-yellow)](https://huggingface.co/Alibaba-Apsara/DASD-4B-Thinking)  [![ModelScope Model](https://img.shields.io/badge/🤖%20Checkpoint-DASD--4B--Thinking-624aff)](https://www.modelscope.cn/models/Alibaba-Apsara/DASD-4B-Thinking)  [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Checkpoint-DASD--30B--A3B--Thinking--Preview-yellow)](https://huggingface.co/Alibaba-Apsara/DASD-30B-A3B-Thinking-Preview)  [![ModelScope Model](https://img.shields.io/badge/🤖%20Checkpoint-DASD--30B--A3B--Thinking--Preview-624aff)](https://www.modelscope.cn/models/Alibaba-Apsara/DASD-30B-A3B-Thinking-Preview)  [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-Superior--Reasoning--SFT--gpt--oss--120b-red)](https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b)  [![ModelScope Model](https://img.shields.io/badge/🤖%20Dataset-Superior--Reasoning--SFT--gpt--oss--120b-124aff)](https://www.modelscope.cn/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b)  [![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-Superior--Reasoning--SFT--gpt--oss--120b--Logprob-red)](https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob)  [![ModelScope Model](https://img.shields.io/badge/🤖%20Dataset-Superior--Reasoning--SFT--gpt--oss--120b--Logprob-124aff)](https://www.modelscope.cn/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob)  ## 🚀 Overview This dataset contains the **token-level log-probabilities** generated by the teacher model (**gpt-oss-120b**) for the reasoning samples in the main **[Superior-Reasoning-SFT-gpt-oss-120b](https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b)** Dataset. ## 🔗 Relationship to Main Dataset This dataset is a **companion** to the main `Superior-Reasoning-SFT-gpt-oss-120b` dataset. Records are linked via a unique `sample_uuid`. * **Main Dataset**: Contains the text (prompts, responses), domain info, and high-level metadata. * **Logprobs Dataset (This)**: Contains the token IDs and their corresponding log-probability values from the teacher. ## 📄 Data Format The data in the DASD-Thinking dataset follows a structured format: ### Example: ```json { "sample_uuid": "e6ebfe0b-62a2-4b8b-ac53-4c8d48facbea", "token_ids": [2167, 1309, ...], "logprobs": [-0.08339496701955795, -1.2306615114212036, ...], } ``` ## 📊 Proven Effectiveness Models trained on this specific dataset recipe achieve State-of-the-Art performance for their size class. ### 4B Dense Model Performance | Model / Setting | AIME24 | AIME25 | LiveCodeBench v5 | LiveCodeBench v6 | GPQA-D | | --------------------------- | -----: | -----: | -----: | -----: | -----: | | Qwen3-4B-Instruct-2507 | - | 47.4 | - | 35.1 | 62.5 | | + Low-Temperature Training (stage 1) | 84.2 | 74.0 | 56.6 | 50.6 | 67.7 | | + High-Temperature Training (stage 2) | 87.7 | 83.0 | 68.4 | 67.2 | 67.6 | ### 30B MoE Model Performance **DASD-30B-A3B-Thinking-Preview** (trained on **Stage 1 data only**) demonstrates incredible data efficiency. | Model | AIME25 | LiveCodeBench v6 | GPQA-D | Average | | ------------------------------------ | -----: | -----: | -----: | ------: | | gpt-oss-20b | 91.7 | 61.0 | 71.5 | 74.7 | | Qwen3-30B-A3B-Thinking-2507 | 85.0 | 66.0 | 73.4 | 74.8 | | NVIDIA-Nemotron-3-Nano-30B-A3B | 89.1 | 68.3 | 73.0 | 76.8 | | DASD-30B-A3B-Thinking-Preview (Ours) | 86.7 | 72.8 | 72.3 | 77.3 | ## 📜 Dataset Access & License The dataset is released under **[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/legalcode)**. ## 📚 Citation DASD-Thinking is developed by Alibaba Cloud, as part of our mission to advance open, efficient, and trustworthy reasoning systems. If you find this work useful in your research or applications, please cite our technical report. ```bibtex @article{yan2026dasd, title={Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning}, author={Yan, Shaotian and Liu, Kaiyuan and Shen, Chen and Wang, Bing and Fan, Sinan and Zhang, Jun and Wu, Yue and Wang, Zheng and Ye, Jieping}, year={2026}, journal={arXiv preprint arXiv:2601.09088}, url={https://arxiv.org/abs/2601.09088} } @article{liu2025where, title={Where Did This Sentence Come From? Tracing Provenance in LLM Reasoning Distillation}, author={Liu, Kaiyuan and Yan, Shaotian and Miao, Rui and Wang, Bing and Shen, Chen and Zhang, Jun and Ye, Jieping}, journal={arXiv preprint arXiv:2512.20908}, year={2025} } ``` We welcome collaboration, feedback, and community contributions to push the boundaries of what small models can reason about—transparently and responsibly.