SERA: Scale-Equalized Rollout Allocation for Maximum Likelihood Reinforcement Learning

arXiv:2609.36552 · cs.LG, cs.AI · Submitted 2026-09-29 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/ChenZihao0121/SERA

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

Terminology

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

Sources

• SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
• The Best of N Worlds: Aligning Reinforcement Learning with Best-of-N Sampling via max@k Optimisation
• Vector Policy Optimization: Training for Diversity Improves Test-Time Search
• Prompt Interference in LLM Post-Training: Why Pass@k Optimization Can Degrade Pass@1
• Evaluating Large Language Models Trained on Code
• Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
• Training Verifiers to Solve Math Word Problems
• What is the objective of reasoning with reinforcement learning?
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Measuring Mathematical Problem Solving With the MATH Dataset
• Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning
• Spend Your Rollouts Where It Counts: Rollout Allocation for Group-Based RL Post-Training
• SetPO: Set-Level Policy Optimization for Diversity-Preserving LLM Reasoning
• Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
• Understanding R1-Zero-Like Training: A Critical Perspective
• Uniform-Correct Policy Optimization: Breaking RLVR's Indifference to Diversity
• Proximal Policy Optimization Algorithms
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Maximum Likelihood Reinforcement Learning

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