arXiv Machine Learning June 5, 2026 By Chirag Chawla, Rohan Charudatt Salvi, Madhav S. Baidya

Selective-Advantage Entropy-Adaptive Horizon GRPO: Asymmetric Token-Level Discounting for Efficient Reinforcement Learning of Language Models

Read the original on arXiv Machine Learning →

arXiv:2606. 05434v1 Announce Type: new Abstract: Group Relative Policy Optimisation (GRPO) has emerged as an effective reinforcement-learning algorithm for aligning language models on reasoning tasks, but it treats every token position and every sampled rollout symmetrically.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Aug 7

All-Quadrant Bounded Clipping GRPO: Closing the Unbounded Blind Spot for Stable and Generalizable Training

arXiv:2601. 03895v2 Announce Type: replace-cross Abstract: Group Relative Policy Optimization (GRPO) has emerged as a popular algorithm for reinforcement learning with large language models (LLMs).

By Chi Liu, Xin Chen

llms reinforcement-learning benchmarks

arXiv Machine Learning

Jun 16

A Gradient Perspective on RLVR Stability and Winner Advantage Policy Optimization

arXiv:2606. 16154v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves language-model reasoning, but GRPO-style optimization remains prone to collapse.

By Prasanth YSS, Zhichen Ren, Rasa Hosseinzadeh, Ilan Gofman, Yuqi Chen, Zhaoyan Liu, Guangwei Yu, Jesse C. Cresswell, Satya Krishna Gorti

reinforcement-learning benchmarks

arXiv AI

Jul 29

AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning

arXiv:2607. 24833v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards is a powerful paradigm for eliciting reasoning in large language models, yet it suffers from severe reward sparsity on competition-level mathematics.

By Zibin Meng, Zhenyu Zhao, Chunqiang Run

llms reinforcement-learning efficiency benchmarks safety

arXiv Machine Learning

Jul 30

ReCo: Reweighting GRPO Against Distributional Concentration

arXiv:2607. 26862v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a standard reinforcement learning method for post-training language models.

By Junoh Park, Junseo Hwang, Wonguk Cho, Taesup Kim

llms reinforcement-learning benchmarks

arXiv Machine Learning

Jun 25

ExTra: Exploratory Trajectory Optimization for Language Model Reinforcement Learning

arXiv:2606. 24994v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) for language-model reasoning can fail at both extremes of task difficulty: easy prompts often produce all-correct, low-diversity rollout groups with little gradient signal, while hard prompts can produce all-incorrect groups with no positive reward.

By Wenyang Hu, Junxiang Jia, Zhen Shu, Daniel Dahlmeier, See-Kiong Ng, Bryan Kian Hsiang Low

llms rag reinforcement-learning benchmarks

arXiv Machine Learning

Jun 2

Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation

arXiv:2605. 21125v2 Announce Type: replace Abstract: Group Relative Policy Optimization (GRPO), a prominent algorithm within the Reinforcement Learning from Verifiable Rewards (RLVR) framework, has achieved strong results in improving the reasoning capabilities of large language models (LLMs).

By Xixiang He, Qiyao Sun, Ao Cheng, Xingming Li, Xuanyu Ji, Hailun Lu, Runke Huang, Qingyong Hu

llms reinforcement-learning benchmarks

Related stories

All-Quadrant Bounded Clipping GRPO: Closing the Unbounded Blind Spot for Stable and Generalizable Training

A Gradient Perspective on RLVR Stability and Winner Advantage Policy Optimization

AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning

ReCo: Reweighting GRPO Against Distributional Concentration

ExTra: Exploratory Trajectory Optimization for Language Model Reinforcement Learning

Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation