Cited by: MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

12 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.

• Group Sequence Policy Optimization
  arxiv:2507.18071 · evidence: id
• AlphaGo Moment for Model Architecture Discovery
  arxiv:2507.18074 · evidence: id
• Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization
  arxiv:2508.07629 · evidence: title
• On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
  arxiv:2508.11408 · evidence: id
• Single-stream Policy Optimization
  arxiv:2509.13232 · evidence: id
• The Art of Scaling Reinforcement Learning Compute for LLMs
  arxiv:2510.13786 · evidence: id
• ESPO: Entropy Importance Sampling Policy Optimization
  arxiv:2512.00499 · evidence: id
• Toward Training Superintelligent Software Agents through Self-Play SWE-RL
  arxiv:2512.18552 · evidence: id
• Reinforcement Learning via Self-Distillation
  arxiv:2601.20802 · evidence: id
• Skip-Connected Policy Optimization for Implicit Advantage
  arxiv:2604.08690 · evidence: id
• Revisiting Reinforcement Learning with Verifiable Rewards from a Contrastive Perspective
  arxiv:2605.12969 · evidence: id
• GRPO++: Tricks for Making RL Actually Work (Cameron Wolfe)
  url:cameronrwolfe.substack.com/p/grpo-tricks · evidence: id