1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Han, Wang, Haotian, Peng, Yiping, Zhao, Sitong, Tian, Xiaoyu, Chen, Shuaiting, Ji, Yunjie, Li, Xiangang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
by: Tian, Xiaoyu, et al.
Published: (2025)
by: Tian, Xiaoyu, et al.
Published: (2025)
Not All Correct Answers Are Equal: Why Your Distillation Source Matters
by: Tian, Xiaoyu, et al.
Published: (2025)
by: Tian, Xiaoyu, et al.
Published: (2025)
Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability
by: Wang, Haotian, et al.
Published: (2025)
by: Wang, Haotian, et al.
Published: (2025)
Exploring the Potential of Offline RL for Reasoning in LLMs: A Preliminary Study
by: Tian, Xiaoyu, et al.
Published: (2025)
by: Tian, Xiaoyu, et al.
Published: (2025)
AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
by: Ji, Yunjie, et al.
Published: (2025)
by: Ji, Yunjie, et al.
Published: (2025)
Think Twice: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking
by: Tian, Xiaoyu, et al.
Published: (2025)
by: Tian, Xiaoyu, et al.
Published: (2025)
How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study
by: Ji, Yunjie, et al.
Published: (2025)
by: Ji, Yunjie, et al.
Published: (2025)
Personalised Distillation: Empowering Open-Sourced LLMs with Adaptive Learning for Code Generation
by: Chen, Hailin, et al.
Published: (2023)
by: Chen, Hailin, et al.
Published: (2023)
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
by: Zhao, Siyan, et al.
Published: (2026)
by: Zhao, Siyan, et al.
Published: (2026)
Memorizing is Not Enough: Deep Knowledge Injection Through Reasoning
by: Xu, Ruoxi, et al.
Published: (2025)
by: Xu, Ruoxi, et al.
Published: (2025)
Latent Distance Guided Alignment Training for Large Language Models
by: Luo, Haotian
Published: (2024)
by: Luo, Haotian
Published: (2024)
Training with Harnesses: On-Policy Harness Self-Distillation for Complex Reasoning
by: Zhao, Zhengyang, et al.
Published: (2026)
by: Zhao, Zhengyang, et al.
Published: (2026)
WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
by: Deng, Yuntian, et al.
Published: (2024)
by: Deng, Yuntian, et al.
Published: (2024)
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
by: Wang, Jun, et al.
Published: (2024)
by: Wang, Jun, et al.
Published: (2024)
ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting
by: Cheng, Xiaoxue, et al.
Published: (2024)
by: Cheng, Xiaoxue, et al.
Published: (2024)
RedPajama: an Open Dataset for Training Large Language Models
by: Weber, Maurice, et al.
Published: (2024)
by: Weber, Maurice, et al.
Published: (2024)
Compute-Accuracy Pareto Frontiers for Open-Source Reasoning Large Language Models
by: Prucs, Ákos, et al.
Published: (2025)
by: Prucs, Ákos, et al.
Published: (2025)
Evaluating and Mitigating Social Bias for Large Language Models in Open-ended Settings
by: Liu, Zhao, et al.
Published: (2024)
by: Liu, Zhao, et al.
Published: (2024)
F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data
by: Zhang, Ziyin, et al.
Published: (2025)
by: Zhang, Ziyin, et al.
Published: (2025)
SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning
by: Wen, Cheng, et al.
Published: (2025)
by: Wen, Cheng, et al.
Published: (2025)
MentraSuite: Post-Training Large Language Models for Mental Health Reasoning and Assessment
by: Xiao, Mengxi, et al.
Published: (2025)
by: Xiao, Mengxi, et al.
Published: (2025)
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
by: Islam, Shayekh Bin, et al.
Published: (2024)
by: Islam, Shayekh Bin, et al.
Published: (2024)
From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models
by: Zhu, Wenxin, et al.
Published: (2025)
by: Zhu, Wenxin, et al.
Published: (2025)
Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training
by: Yu, Yao-Ching, et al.
Published: (2025)
by: Yu, Yao-Ching, et al.
Published: (2025)
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
by: Wang, Guan, et al.
Published: (2023)
by: Wang, Guan, et al.
Published: (2023)
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
by: Wang, Yiping, et al.
Published: (2025)
by: Wang, Yiping, et al.
Published: (2025)
InternLM-Law: An Open Source Chinese Legal Large Language Model
by: Fei, Zhiwei, et al.
Published: (2024)
by: Fei, Zhiwei, et al.
Published: (2024)
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models
by: Wang, Chengyu, et al.
Published: (2025)
by: Wang, Chengyu, et al.
Published: (2025)
OpenThaiGPT 1.6 and R1: Thai-Centric Open Source and Reasoning Large Language Models
by: Yuenyong, Sumeth, et al.
Published: (2025)
by: Yuenyong, Sumeth, et al.
Published: (2025)
Measuring Maximum Activations in Open Large Language Models
by: Chen, Luxuan, et al.
Published: (2026)
by: Chen, Luxuan, et al.
Published: (2026)
MMCR: Benchmarking Cross-Source Reasoning in Scientific Papers
by: Tian, Yang, et al.
Published: (2025)
by: Tian, Yang, et al.
Published: (2025)
ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
by: Chen, Hailin, et al.
Published: (2023)
by: Chen, Hailin, et al.
Published: (2023)
Surgical Post-Training: Proximal On-Policy Distillation for Reasoning with Knowledge Retention
by: Lin, Wenye, et al.
Published: (2026)
by: Lin, Wenye, et al.
Published: (2026)
Optimizing Large Language Model Training Using FP4 Quantization
by: Wang, Ruizhe, et al.
Published: (2025)
by: Wang, Ruizhe, et al.
Published: (2025)
Training Large Language Models to Reason in a Continuous Latent Space
by: Hao, Shibo, et al.
Published: (2024)
by: Hao, Shibo, et al.
Published: (2024)
Automatically Interpreting Millions of Features in Large Language Models
by: Paulo, Gonçalo, et al.
Published: (2024)
by: Paulo, Gonçalo, et al.
Published: (2024)
MobileLLM-R1: Exploring the Limits of Sub-Billion Language Model Reasoners with Open Training Recipes
by: Zhao, Changsheng, et al.
Published: (2025)
by: Zhao, Changsheng, et al.
Published: (2025)
TRAM: Benchmarking Temporal Reasoning for Large Language Models
by: Wang, Yuqing, et al.
Published: (2023)
by: Wang, Yuqing, et al.
Published: (2023)
Structured In-context Environment Scaling for Large Language Model Reasoning
by: Yu, Peng, et al.
Published: (2025)
by: Yu, Peng, et al.
Published: (2025)
Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning
by: Tan, Xingyu, et al.
Published: (2024)
by: Tan, Xingyu, et al.
Published: (2024)
Similar Items
-
DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
by: Tian, Xiaoyu, et al.
Published: (2025) -
Not All Correct Answers Are Equal: Why Your Distillation Source Matters
by: Tian, Xiaoyu, et al.
Published: (2025) -
Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability
by: Wang, Haotian, et al.
Published: (2025) -
Exploring the Potential of Offline RL for Reasoning in LLMs: A Preliminary Study
by: Tian, Xiaoyu, et al.
Published: (2025) -
AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
by: Ji, Yunjie, et al.
Published: (2025)