Frontier Learning: Training LLM Reasoners at the Edge of Capability
cs.LG, cs.AI, cs.CL
Submitted: 2026-09-28
Updated: 2026-09-28
Terminology
Sources
- Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning
- Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics
- AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering
- Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
- Self-Evolving Curriculum for LLM Reasoning
- Harder Is Better: Boosting Mathematical Reasoning via Difficulty-Aware GRPO and Multi-Aspect Question Reformulation
- Learning to Reason at the Frontier of Learnability
- The Llama 3 Herd of Models
- Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training
- rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
- REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization
- R-Zero: Self-Evolving Reasoning LLM from Zero Data
- AdaCuRL: Adaptive Curriculum Reinforcement Learning with Invalid Sample Mitigation and Historical Revisiting
- Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
- SPADE: Self-Play in Adaptive Synthetic Executable Environments
- SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
- ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
- WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
- Teacher-Student Curriculum Learning
- Olmo 3
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