Group Relative Policy Optimization

Also known as GRPO

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Latest papers 305

48 papers in the last four weeks, up 109% on the four weeks before. 0.3% of all new papers.

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dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models
May 10, 2026Zhengyan Wan, Yidong Ouyang, Panwen Hu +1Group Relative Policy Optimization Image Generation
Mohamed bin Zayed University of Artificial Intelligence · East China Normal University · University of California, Los Angeles +1
CoDistill-GRPO: A Co-Distillation Recipe for Efficient Group Relative Policy Optimization
May 9, 2026Soo Min Kwon, Ziteng Sun, Ananda Theertha Suresh +2RL for Language Model Reasoning Group Relative Policy Optimization
University of Michigan, Ann Arbor · *Work done during an internship at Google · Google Research +1
DUET: Optimize Token-Budget Allocation for Reinforcement Learning with Verifiable Rewards
May 8, 2026Haoyu Hu, Xuandong Zhao, Xuhai "Orson'' Xu +1Reinforcement Learning Group Relative Policy Optimization
Cornell University · University of California, Berkeley · Columbia University
Interactive Critique-Revision Training for Reliable Structured LLM Generation
May 8, 2026Fei Xu Yu, Zuyuan Zhang, Mahdi Imani +2LLM Self-Refinement Group Relative Policy Optimization
The George Washington University · Northeastern University · United States Military Academy
Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works
May 8, 2026Wenhua Nie, Jianan Wu, Junlin Liu +6Reinforcement Learning Group Relative Policy Optimization
National Taiwan University
Gradient-Based LoRA Rank Allocation Under GRPO: An Empirical Study
May 8, 2026Yash Ganpat SawantGroup Relative Policy Optimization Low-Rank Adaptation
1Independent Researcher.
Signal Reshaping for GRPO in Weak-Feedback Agentic Code Repair
May 8, 2026Jia Li, Yuxin Su, Ting Peng +3RL for Code Generation Reward Shaping
The Chinese University of Hong Kong · Sun Yat-sen University · Tencent
Where to Spend Rollouts: Hit-Utility Optimal Rollout Allocation for Group-Based RLVR
May 8, 2026Tao Wang, Shuo Li, Yan Sun +2RL for Language Model Reasoning Group Relative Policy Optimization
University of Pennsylvania · New Jersey Institute of Technology · University of Tennessee, Knoxville
DACA-GRPO: Denoising-Aware Credit Assignment for Reinforcement Learning in Diffusion Language Models
May 8, 2026Amin Karimi Monsefi, Dominic Culver, Nikhil Bhendawade +4Group Relative Policy Optimization Credit Assignment in RL
The Ohio State University · Apple
A Unified Pair-GRPO Family: From Implicit to Explicit Preference Constraints for Stable and General RL Alignment
May 7, 2026Hao YuPairwise Preference Learning LLM Alignment
Department of Automation, Tsinghua University
Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex
May 7, 2026Yun Qu, Qi Wang, Yixiu Mao +11RL for Language Model Reasoning Group Relative Policy Optimization
Department of Automation, Tsinghua University · 2LLM Department, Tencent
Selective Rollout: Mid-Trajectory Termination for Multi-Sample Agent RL
May 7, 2026Zhiyuan Zhai, Xin WangReinforcement Learning Group Relative Policy Optimization
Fudan University
MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery
May 7, 2026Nanjie Yao, Junlong Ren, Wenhao Shen +1Diffusion Model Guidance Markerless Motion Capture
The Hong Kong University of Science and Technology (Guangzhou), China · Nanyang Technological University, Singapore
EP-GRPO: Entropy-Progress Aligned Group Relative Policy Optimization with Implicit Process Guidance
May 6, 2026Song Yu, Li Li, Wenwen Zhao +1RL for Language Model Reasoning Group Relative Policy Optimization
School of Computer and Information Science, Southwest University, Chongqing 400715, China
Maximizing Rollout Informativeness under a Fixed Budget: A Submodular View of Tree Search for Tool-Use Agentic Reinforcement Learning
May 6, 2026Yuelin Hu, Zhenbo Yu, Zhengxue Cheng +2Tree Search Group Relative Policy Optimization
Shanghai Jiao Tong University · Shanghai Maritime University
GRPO-TTA: Test-Time Visual Tuning for Vision-Language Models via GRPO-Driven Reinforcement Learning
May 5, 2026Yujun Li, Hongyuan Zhang, Yuan YuanVLM Adaptation Test-Time Adaptation of VLMs
School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, P.R. China · The University of Hong Kong
Faithful Mobile GUI Agents with Guided Advantage Estimator
May 2, 2026Haowen Hu, Pengzhou Cheng, Zheng Wu +3Reinforcement Learning RL for GUI Agents
1Shanghai Jiao Tong University.
Uniform-Correct Policy Optimization: Breaking RLVR's Indifference to Diversity
May 1, 2026Anamika Lochab, Bolian Li, Ruqi ZhangRL for Language Model Reasoning Group Relative Policy Optimization
Department of Computer Science Purdue University, West Lafayette
Cost-Aware Learning
Apr 30, 2026Clara Mohri, Amir Globerson, Haim Kaplan +2Stochastic Optimization RL for Language Models
Kempner Institute · Harvard University · Google Research +1
Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning
Apr 30, 2026Jingcheng Deng, Zihao Wei, Liang Pang +4Reinforcement Learning RL for Language Model Reasoning
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences
V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think
Apr 25, 2026Bingda Tang, Yuhui Zhang, Xiaohan Wang +3Diffusion Model Alignment Group Relative Policy Optimization
Stanford University · Tsinghua University · Amazon FAR +1
Hidden States Know Where Reasoning Diverges: Credit Assignment via Span-Level Wasserstein Distance
Apr 25, 2026Xinzhu Chen, Wei He, Huichuan Fan +7Token-Level Credit Assignment Group Relative Policy Optimization
Beijing University of Posts and Telecommunications · Meituan · Tianjin University +3
Language as a Latent Variable for Reasoning Optimization
Apr 23, 2026Linjuan Wu, Haoran Wei, Jialong Tang +4Multilingual Language Models Cross-Lingual Reasoning in Language Models
Zhejiang University · Tongyi Lab, Alibaba Grou.
Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning
Apr 23, 2026Yongcan Yu, Lingxiao He, Jian Liang +5Reinforcement Learning RL for Language Model Reasoning
1NLPR & MAIS, Institute of Automation, Chinese Academy of Sciences · *Work done during an internship at Meituan · School of Artificial Intelligence, University of Chinese Academy of Sciences +2
GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning
Apr 22, 2026Jingyi Wang, Lei Zhu, Tengjin Weng +8RL for Language Model Reasoning Group Relative Policy Optimization
Tsinghua University · Huawei Noah’s Ark Lab · Shenzhen University
Rethinking Reinforcement Fine-Tuning in LVLM: Convergence, Reward Decomposition, and Generalization
Apr 21, 2026Carter Adams, Rafael Oliveira, Gabriel Almeida +1Tool Use in VLMs Reinforcement Learning
Federal University of Bahia
M $^{2}$ GRPO: Mamba-based Multi-Agent Group Relative Policy Optimization for Biomimetic Underwater Robots Pursuit
Apr 21, 2026Yukai Feng, Zhiheng Wu, Zhengxing Wu +2Multi-Robot Systems Group Relative Policy Optimization
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China, and also with the Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China · State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China
Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training
Apr 21, 2026Yunbo Long, Tejumade Afonja, Guangya Hao +2Tabular Foundation Models Group Relative Policy Optimization
Department of Engineering, University of Cambridge · CISPA Helmholtz Center for Information Security, Saarbrücken, Germany · The Alan Turing Institute, London
Bounded Ratio Reinforcement Learning
Apr 20, 2026Yunke Ao, Le Chen, Bruce D. Lee +5Reinforcement Learning Group Relative Policy Optimization
ETH Zurich · MPI for Intelligent Systems · University of Alberta +2
UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
Apr 20, 2026Jiaqi Wang, Haoge Deng, Ting Pan +5T2I Generation Group Relative Policy Optimization
Beijing University of Posts and Telecommunications · Beijing Academy of Artificial Intelligence

May 10, 2026J/K move · Enter open · S save

dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models

Zhengyan Wan, Yidong Ouyang, Panwen Hu, Qiang Sun

Mohamed bin Zayed University of Artificial Intelligence · East China Normal University · University of California, Los Angeles+1

Group Relative Policy Optimization Image Generation Flow-Based Generative Modeling RL for Generative Models Multimodal Understanding

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Discrete flow models (DFMs) are a class of flexible generative models for generating discrete data, and diffusion large language models (dLLMs) can be viewed as a special case with a specific choice of a mixture path and a masked source distribution. While several recent works have explored reinforcement learning for dLLMs, its application to more general discrete flow models remains underexplored. In this work, we present discrete Flow-GRPO (dFlowGRPO), a unified reinforcement learning framework for discrete flow models that supports a broad family of probability paths and non-masked source distributions. We derive the full trajectory probability for DFMs and formulate the denoising process as a Markov decision process, enabling dFlowGRPO to incorporate information from both the associated conditional transition rates and the posterior model during reinforcement learning. We apply dFlowGRPO to FUDOKI, a recent multimodal discrete flow model, and evaluate it on both image generation and multimodal understanding tasks. Empirical results show that dFlowGRPO outperforms existing GRPO-type methods for dLLMs on text-to-image generation tasks and achieves performance competitive with continuous flow-based models trained using Flow-GRPO, while also demonstrating strong capabilities on understanding tasks.