Cited by: Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

11 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.

• Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
  arxiv:2504.13837 · evidence: title
• 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
• On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
  arxiv:2508.11408 · evidence: id
• Emergent Hierarchical Reasoning in LLMs through Reinforcement Learning
  arxiv:2509.03646 · evidence: id
• ESPO: Entropy Importance Sampling Policy Optimization
  arxiv:2512.00499 · evidence: id
• Reinforcement Learning via Self-Distillation
  arxiv:2601.20802 · evidence: title
• Skip-Connected Policy Optimization for Implicit Advantage
  arxiv:2604.08690 · evidence: id
• GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning
  arxiv:2604.20659 · evidence: id
• Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning
  arxiv:2605.06241 · evidence: id
• From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
  arxiv:2605.22074 · evidence: id