Cover Image

RLoop: An Self-Improving Framework for Reinforcement Learning with Iterative Policy Initialization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhiyuan, Zeng, Liu, Jiashuo, Yin, Zhangyue, Zhang, Ge, Huang, Wenhao, Qiu, Xipeng
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO
by: Zeng, Zhiyuan, et al.
Published: (2026)

ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models
by: Yin, Zhangyue, et al.
Published: (2025)

Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?
by: Zeng, Zhiyuan, et al.
Published: (2025)

Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
by: Zeng, Zhiyuan, et al.
Published: (2024)

Mitigating LLM Hallucination via Behaviorally Calibrated Reinforcement Learning
by: Wu, Jiayun, et al.
Published: (2025)

BandPO: Bridging Trust Regions and Ratio Clipping via Probability-Aware Bounds for LLM Reinforcement Learning
by: Li, Yuan, et al.
Published: (2026)

Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
by: Sun, Qiushi, et al.
Published: (2023)

R3-RAG: Learning Step-by-Step Reasoning and Retrieval for LLMs via Reinforcement Learning
by: Li, Yuan, et al.
Published: (2025)

LLatrieval: LLM-Verified Retrieval for Verifiable Generation
by: Li, Xiaonan, et al.
Published: (2023)

TabularMath: Evaluating Computational Extrapolation in Tabular Learning via Program-Verified Synthesis
by: Cheng, Zerui, et al.
Published: (2026)

Turn Waste into Worth: Rectifying Top-$k$ Router of MoE
by: Zeng, Zhiyuan, et al.
Published: (2024)

VeRA: Verified Reasoning Data Augmentation at Scale
by: Cheng, Zerui, et al.
Published: (2026)

Can AI Assistants Know What They Don't Know?
by: Cheng, Qinyuan, et al.
Published: (2024)

FamilyTool: A Multi-hop Personalized Tool Use Benchmark
by: Wang, Yuxin, et al.
Published: (2025)

APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents
by: Li, Yibo, et al.
Published: (2026)

VehicleWorld: A Highly Integrated Multi-Device Environment for Intelligent Vehicle Interaction
by: Yang, Jie, et al.
Published: (2025)

Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy
by: Cai, Ruichu, et al.
Published: (2024)

Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
by: Jin, Luozhijie, et al.
Published: (2025)

Pessimistic Auxiliary Policy for Offline Reinforcement Learning
by: Zhang, Fan, et al.
Published: (2026)

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
by: Yao, Yihang, et al.
Published: (2023)

How to Set the Learning Rate for Large-Scale Pre-training?
by: Zhou, Yunhua, et al.
Published: (2026)

LLM Embeddings Improve Test-time Adaptation to Tabular $Y|X$-Shifts
by: Zeng, Yibo, et al.
Published: (2024)

A Survey on Self-play Methods in Reinforcement Learning
by: Zhang, Ruize, et al.
Published: (2024)

Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning
by: Fei, Zhaoye, et al.
Published: (2025)

Data Heterogeneity Modeling for Trustworthy Machine Learning
by: Liu, Jiashuo, et al.
Published: (2025)

Real-Time Iteration Scheme for Diffusion Policy
by: Duan, Yufei, et al.
Published: (2025)

Emergent Structured Representations Support Flexible In-Context Inference in Large Language Models
by: Xu, Ningyu, et al.
Published: (2026)

Dynamic and Generalizable Process Reward Modeling
by: Yin, Zhangyue, et al.
Published: (2025)

Agent-Driven Autonomous Reinforcement Learning Research: Iterative Policy Improvement for Quadruped Locomotion
by: Khandelwal, Nimesh, et al.
Published: (2026)

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
by: Du, Mingzhe, et al.
Published: (2025)

Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
by: Liu, Zifan, et al.
Published: (2024)

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security
by: Dai, Muzhi, et al.
Published: (2025)

Reinforcement Learning for Self-Improving Agent with Skill Library
by: Wang, Jiongxiao, et al.
Published: (2025)

RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback
by: Liu, Yanming, et al.
Published: (2024)

Optimising Call Centre Operations using Reinforcement Learning: Value Iteration versus Proximal Policy Optimisation
by: Li, Kwong Ho, et al.
Published: (2025)

Iterative Batch Reinforcement Learning via Safe Diversified Model-based Policy Search
by: Najib, Amna, et al.
Published: (2024)

Diffusion Policies with Value-Conditional Optimization for Offline Reinforcement Learning
by: Ma, Yunchang, et al.
Published: (2025)

The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping
by: Liu, Yang, et al.
Published: (2026)

Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models
by: Tan, Lit Sin, et al.
Published: (2026)

VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks
by: Zhang, Shiduo, et al.
Published: (2024)