When Does Momentum Help in Reinforcement Learning with Verifiable Rewards?

arXiv:2610.20413 · cs.LG, cs.AI, math.OC, stat.ML · Submitted 2026-10-14 · Read on arXiv

cs.LG, cs.AI, math.OC, stat.ML

Submitted: 2026-10-14

Updated: 2026-10-14

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes

Sources

• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR
• Logarithmic-time Schedules for Scaling Language Models with Momentum
• Tulu 3: Pushing Frontiers in Open Language Model Post-Training
• Qwen2.5 Technical Report
• Proximal Policy Optimization Algorithms
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
• Parameter Exploration for RLVR via Variational Learning
• Qwen3 Technical Report
• ISO: An RLVR-Native Optimization Stack
• Fine-Tuning Language Models from Human Preferences

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