Cover Image

A Relative-Budget Theory for Reinforcement Learning with Verifiable Rewards in Large Language Model Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wachi, Akifumi, Kinoshita, Hirota, Takakura, Shokichi, Higuchi, Rei, Suzuki, Taiji
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis
by: Higuchi, Rei, et al.
Published: (2026)

Inference-Aware Meta-Alignment of LLMs via Non-Linear GRPO
by: Takakura, Shokichi, et al.
Published: (2026)

Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language Models
by: Higuchi, Rei, et al.
Published: (2025)

Stepwise Alignment for Constrained Language Model Policy Optimization
by: Wachi, Akifumi, et al.
Published: (2024)

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing
by: Tran, Thien Q., et al.
Published: (2025)

Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
by: Takakura, Shokichi, et al.
Published: (2024)

Approximation and Estimation Ability of Transformers for Sequence-to-Sequence Functions with Infinite Dimensional Input
by: Takakura, Shokichi, et al.
Published: (2023)

A Survey of Constraint Formulations in Safe Reinforcement Learning
by: Wachi, Akifumi, et al.
Published: (2024)

A Provable Approach for End-to-End Safe Reinforcement Learning
by: Wachi, Akifumi, et al.
Published: (2025)

Long-term Safe Reinforcement Learning with Binary Feedback
by: Wachi, Akifumi, et al.
Published: (2024)

REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
by: Stojanovski, Zafir, et al.
Published: (2025)

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
by: Ma, Zhengzhao, et al.
Published: (2026)

Target Return Optimizer for Multi-Game Decision Transformer
by: Tatematsu, Kensuke, et al.
Published: (2025)

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
by: Gunjal, Anisha, et al.
Published: (2025)

Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards
by: Nguyen, Hieu Trung, et al.
Published: (2026)

Gradient Regularization Prevents Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
by: Ackermann, Johannes, et al.
Published: (2026)

Masked-and-Reordered Self-Supervision for Reinforcement Learning from Verifiable Rewards
by: Wang, Zhen, et al.
Published: (2025)

ProofSketch: Efficient Verified Reasoning for Large Language Models
by: Sheshanarayana, Disha, et al.
Published: (2025)

DUET: Optimize Token-Budget Allocation for Reinforcement Learning with Verifiable Rewards
by: Hu, Haoyu, et al.
Published: (2026)

Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine
by: Alsadat, Shayan Meshkat, et al.
Published: (2024)

Rate or Fate? RLV$^\varepsilon$R: Reinforcement Learning with Verifiable Noisy Rewards
by: Rad, Ali, et al.
Published: (2026)

RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning
by: Zha, Kaiwen, et al.
Published: (2025)

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance
by: Yan, Kai, et al.
Published: (2026)

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning
by: Kudo, Mikoto, et al.
Published: (2026)

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)

Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning
by: Mo, Shentong
Published: (2026)

Reinforcement Learning for Reasoning in Large Language Models with One Training Example
by: Wang, Yiping, et al.
Published: (2025)

Meta-Reasoning Improves Tool Use in Large Language Models
by: Alazraki, Lisa, et al.
Published: (2024)

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
by: Wen, Xumeng, et al.
Published: (2025)

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning
by: Liu, Wei, et al.
Published: (2025)

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models
by: Yeh, Cheng-Kai, et al.
Published: (2025)

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
by: Xi, Zhiheng, et al.
Published: (2024)

Optimizing Anytime Reasoning via Budget Relative Policy Optimization
by: Qi, Penghui, et al.
Published: (2025)

Self-Rewarding Rubric-Based Reinforcement Learning for Open-Ended Reasoning
by: Ye, Zhiling, et al.
Published: (2025)

From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
by: Jiang, Xitai, et al.
Published: (2026)

A Survey of Reinforcement Learning for Large Reasoning Models
by: Zhang, Kaiyan, et al.
Published: (2025)

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models
by: Jin, Renren, et al.
Published: (2025)

The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
by: Cui, Ganqu, et al.
Published: (2025)

Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
by: Liu, Xiaoyuan, et al.
Published: (2025)

Rewarding Intellectual Humility Learning When Not To Answer In Large Language Models
by: Jha, Abha, et al.
Published: (2026)