KDRL: Post-Training Reasoning LLMs via Unified Knowledge Distillation and Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Hongling, Zhu, Qi, Deng, Heyuan, Li, Jinpeng, Hou, Lu, Wang, Yasheng, Shang, Lifeng, Xu, Ruifeng, Mi, Fei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Teaching Large Reasoning Models Effective Reflection
by: Wang, Hanbin, et al.
Published: (2026)
by: Wang, Hanbin, et al.
Published: (2026)
DAST: Difficulty-Aware Self-Training on Large Language Models
by: Xue, Boyang, et al.
Published: (2025)
by: Xue, Boyang, et al.
Published: (2025)
Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning
by: Ding, Bowen, et al.
Published: (2025)
by: Ding, Bowen, et al.
Published: (2025)
Group Pattern Selection Optimization: Let LRMs Pick the Right Pattern for Reasoning
by: Wang, Hanbin, et al.
Published: (2026)
by: Wang, Hanbin, et al.
Published: (2026)
RLKD: Distilling LLMs' Reasoning via Reinforcement Learning
by: Xu, Shicheng, et al.
Published: (2025)
by: Xu, Shicheng, et al.
Published: (2025)
Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios
by: Huang, Shijue, et al.
Published: (2024)
by: Huang, Shijue, et al.
Published: (2024)
Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning
by: Yu, Erxin, et al.
Published: (2025)
by: Yu, Erxin, et al.
Published: (2025)
The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs
by: Chen, Jierun, et al.
Published: (2025)
by: Chen, Jierun, et al.
Published: (2025)
Distilling Fine-grained Sentiment Understanding from Large Language Models
by: Zhang, Yice, et al.
Published: (2024)
by: Zhang, Yice, et al.
Published: (2024)
Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving
by: Xu, Xin, et al.
Published: (2025)
by: Xu, Xin, et al.
Published: (2025)
ReliableMath: Benchmark of Reliable Mathematical Reasoning on Large Language Models
by: Xue, Boyang, et al.
Published: (2025)
by: Xue, Boyang, et al.
Published: (2025)
EssayBench: Evaluating Large Language Models in Multi-Genre Chinese Essay Writing
by: Gao, Fan, et al.
Published: (2025)
by: Gao, Fan, et al.
Published: (2025)
DS$^2$-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis
by: Xu, Hongling, et al.
Published: (2024)
by: Xu, Hongling, et al.
Published: (2024)
QFFT, Question-Free Fine-Tuning for Adaptive Reasoning
by: Liu, Wanlong, et al.
Published: (2025)
by: Liu, Wanlong, et al.
Published: (2025)
DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning
by: Shi, Wenxuan, et al.
Published: (2025)
by: Shi, Wenxuan, et al.
Published: (2025)
Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification
by: Liu, Chengwu, et al.
Published: (2025)
by: Liu, Chengwu, et al.
Published: (2025)
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)
Stepwise Reasoning Checkpoint Analysis: A Test Time Scaling Method to Enhance LLMs' Reasoning
by: Wang, Zezhong, et al.
Published: (2025)
by: Wang, Zezhong, et al.
Published: (2025)
EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL
by: Xu, Minrui, et al.
Published: (2026)
by: Xu, Minrui, et al.
Published: (2026)
TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning
by: Zhang, Junru, et al.
Published: (2025)
by: Zhang, Junru, et al.
Published: (2025)
Data Management For Training Large Language Models: A Survey
by: Wang, Zige, et al.
Published: (2023)
by: Wang, Zige, et al.
Published: (2023)
Can Post-Training Transform LLMs into Causal Reasoners?
by: Chen, Junqi, et al.
Published: (2026)
by: Chen, Junqi, et al.
Published: (2026)
Entropy Centroids as Intrinsic Rewards for Test-Time Scaling
by: Zhao, Wenshuo, et al.
Published: (2026)
by: Zhao, Wenshuo, et al.
Published: (2026)
ToolACE-MT: Non-Autoregressive Generation for Agentic Multi-Turn Interaction
by: Zeng, Xingshan, et al.
Published: (2025)
by: Zeng, Xingshan, et al.
Published: (2025)
DocPuzzle: A Process-Aware Benchmark for Evaluating Realistic Long-Context Reasoning Capabilities
by: Zhuang, Tianyi, et al.
Published: (2025)
by: Zhuang, Tianyi, et al.
Published: (2025)
Logics-STEM: Empowering LLM Reasoning via Failure-Driven Post-Training and Document Knowledge Enhancement
by: Xu, Mingyu, et al.
Published: (2026)
by: Xu, Mingyu, et al.
Published: (2026)
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
by: Wu, Juncheng, et al.
Published: (2025)
by: Wu, Juncheng, et al.
Published: (2025)
YODA: Teacher-Student Progressive Learning for Language Models
by: Lu, Jianqiao, et al.
Published: (2024)
by: Lu, Jianqiao, et al.
Published: (2024)
Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning
by: Xu, Shuyao, et al.
Published: (2025)
by: Xu, Shuyao, et al.
Published: (2025)
Revealing the Power of Post-Training for Small Language Models via Knowledge Distillation
by: Rang, Miao, et al.
Published: (2025)
by: Rang, Miao, et al.
Published: (2025)
Reinforcement-aware Knowledge Distillation for LLM Reasoning
by: Zhang, Zhaoyang, et al.
Published: (2026)
by: Zhang, Zhaoyang, et al.
Published: (2026)
Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals
by: Chen, Sirui, et al.
Published: (2026)
by: Chen, Sirui, et al.
Published: (2026)
Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis
by: Zhao, Jiaqi, et al.
Published: (2025)
by: Zhao, Jiaqi, et al.
Published: (2025)
Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation
by: Wei, Jingxuan, et al.
Published: (2024)
by: Wei, Jingxuan, et al.
Published: (2024)
Evaluating the External and Parametric Knowledge Fusion of Large Language Models
by: Zhang, Hao, et al.
Published: (2024)
by: Zhang, Hao, et al.
Published: (2024)
NDRL: Cotton Irrigation and Nitrogen Application with Nested Dual-Agent Reinforcement Learning
by: Xu, Ruifeng, et al.
Published: (2025)
by: Xu, Ruifeng, et al.
Published: (2025)
Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs
by: Yang, Wanli, et al.
Published: (2026)
by: Yang, Wanli, et al.
Published: (2026)
Activation Sensitivity as a Unifying Principle for Post-Training Quantization
by: Xu, Bruce Changlong
Published: (2026)
by: Xu, Bruce Changlong
Published: (2026)
Toward Student-Oriented Teacher Network Training For Knowledge Distillation
by: Dong, Chengyu, et al.
Published: (2022)
by: Dong, Chengyu, et al.
Published: (2022)
Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
by: Ma, Jiabo, et al.
Published: (2024)
by: Ma, Jiabo, et al.
Published: (2024)
Similar Items
-
Teaching Large Reasoning Models Effective Reflection
by: Wang, Hanbin, et al.
Published: (2026) -
DAST: Difficulty-Aware Self-Training on Large Language Models
by: Xue, Boyang, et al.
Published: (2025) -
Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning
by: Ding, Bowen, et al.
Published: (2025) -
Group Pattern Selection Optimization: Let LRMs Pick the Right Pattern for Reasoning
by: Wang, Hanbin, et al.
Published: (2026) -
RLKD: Distilling LLMs' Reasoning via Reinforcement Learning
by: Xu, Shicheng, et al.
Published: (2025)