Cited by: DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

67 citation edges inside this catalog. A title match is weaker evidence than an identifier match. Zero entries does not mean no citations on the web.

• The Llama 3 Herd of Models
  arxiv:2407.21783 · evidence: id
• Training Large Language Models to Reason in a Continuous Latent Space
  arxiv:2412.06769 · evidence: id
• Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
  arxiv:2412.14135 · evidence: title
• 2 OLMo 2 Furious
  arxiv:2501.00656 · evidence: id
• LIMO: Less is More for Reasoning
  arxiv:2502.03387 · evidence: id
• Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
  arxiv:2502.05171 · evidence: id
• LADDER: Self-Improving LLMs Through Recursive Problem Decomposition
  arxiv:2503.00735 · evidence: title
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale
  arxiv:2503.14476 · evidence: id
• Understanding R1-Zero-Like Training: A Critical Perspective
  arxiv:2503.20783 · evidence: id
• Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
  arxiv:2504.13837 · evidence: id
• TTRL: Test-Time Reinforcement Learning
  arxiv:2504.16084 · evidence: id
• Reinforcement Learning for Reasoning in Large Language Models with One Training Example
  arxiv:2504.20571 · evidence: id
• Group-in-Group Policy Optimization for LLM Agent Training
  arxiv:2505.10978 · evidence: id
• The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
  arxiv:2505.15134 · evidence: id
• Learning to Reason without External Rewards
  arxiv:2505.19590 · evidence: id
• Can Large Reasoning Models Self-Train?
  arxiv:2505.21444 · evidence: id
• Reinforcing General Reasoning without Verifiers
  arxiv:2505.21493 · evidence: id
• Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
  arxiv:2506.01939 · evidence: id
• Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback
  arxiv:2506.03106 · evidence: id
• Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
  arxiv:2506.06632 · evidence: id
• Spurious Rewards: Rethinking Training Signals in RLVR
  arxiv:2506.10947 · evidence: id
• MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
  arxiv:2506.13585 · evidence: id
• Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved)
  arxiv:2507.12856 · evidence: id
• Group Sequence Policy Optimization
  arxiv:2507.18071 · evidence: id