Saved in:
| Main Authors: | Zhang, Yuyang, Hu, Yang, Dai, Bo, Li, Na |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.23870 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
by: Zhang, Yuyang, et al.
Published: (2026)
by: Zhang, Yuyang, et al.
Published: (2026)
Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
by: Li, Zeqiao, et al.
Published: (2026)
by: Li, Zeqiao, et al.
Published: (2026)
Evolving Diffusion and Flow Matching Policies for Online Reinforcement Learning
by: Zhang, Chubin, et al.
Published: (2025)
by: Zhang, Chubin, et al.
Published: (2025)
A Model-Based Approach to Imitation Learning through Multi-Step Predictions
by: Balim, Haldun, et al.
Published: (2025)
by: Balim, Haldun, et al.
Published: (2025)
Efficient Online Reinforcement Learning for Diffusion Policy
by: Ma, Haitong, et al.
Published: (2025)
by: Ma, Haitong, et al.
Published: (2025)
Spectral Representation-based Reinforcement Learning
by: Gao, Chenxiao, et al.
Published: (2025)
by: Gao, Chenxiao, et al.
Published: (2025)
Efficient Reward Identification In Max Entropy Reinforcement Learning with Sparsity and Rank Priors
by: Shehab, Mohamad Louai, et al.
Published: (2025)
by: Shehab, Mohamad Louai, et al.
Published: (2025)
Energy-Weighted Flow Matching for Offline Reinforcement Learning
by: Zhang, Shiyuan, et al.
Published: (2025)
by: Zhang, Shiyuan, et al.
Published: (2025)
FM-IRL: Flow-Matching for Reward Modeling and Policy Regularization in Reinforcement Learning
by: Wan, Zhenglin, et al.
Published: (2025)
by: Wan, Zhenglin, et al.
Published: (2025)
Reinforcement Learning for Flow-Matching Policies
by: Pfrommer, Samuel, et al.
Published: (2025)
by: Pfrommer, Samuel, et al.
Published: (2025)
Flow Matching for Offline Reinforcement Learning with Discrete Actions
by: Khan, Fairoz Nower, et al.
Published: (2026)
by: Khan, Fairoz Nower, et al.
Published: (2026)
Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning
by: Dai, Bo, et al.
Published: (2026)
by: Dai, Bo, et al.
Published: (2026)
E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models
by: Zhang, Shengjun, et al.
Published: (2026)
by: Zhang, Shengjun, et al.
Published: (2026)
Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective
by: Huang, Yinan, et al.
Published: (2026)
by: Huang, Yinan, et al.
Published: (2026)
FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies
by: Gao, Chenxiao, et al.
Published: (2026)
by: Gao, Chenxiao, et al.
Published: (2026)
Entropy-Regularized Adjoint Matching for Offline Reinforcement Learning
by: Ghanem, Abdelghani, et al.
Published: (2026)
by: Ghanem, Abdelghani, et al.
Published: (2026)
One-Step Flow Policy Mirror Descent
by: Chen, Tianyi, et al.
Published: (2025)
by: Chen, Tianyi, et al.
Published: (2025)
Efficient Duple Perturbation Robustness in Low-rank MDPs
by: Hu, Yang, et al.
Published: (2024)
by: Hu, Yang, et al.
Published: (2024)
Entropy-Controlled Flow Matching
by: Maduabuchi, Chika
Published: (2026)
by: Maduabuchi, Chika
Published: (2026)
ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
by: Zhang, Tonghe, et al.
Published: (2025)
by: Zhang, Tonghe, et al.
Published: (2025)
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
by: Zhang, Yuyang, et al.
Published: (2024)
by: Zhang, Yuyang, et al.
Published: (2024)
INRFlow: Flow Matching for INRs in Ambient Space
by: Wang, Yuyang, et al.
Published: (2024)
by: Wang, Yuyang, et al.
Published: (2024)
Controllable Flow Matching for Online Reinforcement Learning
by: Wang, Bin, et al.
Published: (2025)
by: Wang, Bin, et al.
Published: (2025)
ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning
by: Chen, Wen-Tse, et al.
Published: (2024)
by: Chen, Wen-Tse, et al.
Published: (2024)
To the Max: Reinventing Reward in Reinforcement Learning
by: Veviurko, Grigorii, et al.
Published: (2024)
by: Veviurko, Grigorii, et al.
Published: (2024)
Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies
by: Li, Zeyang, et al.
Published: (2026)
by: Li, Zeyang, et al.
Published: (2026)
MaxCode: A Max-Reward Reinforcement Learning Framework for Automated Code Optimization
by: Ou, Jiefu, et al.
Published: (2026)
by: Ou, Jiefu, et al.
Published: (2026)
Quantile-Coupled Flow Matching for Distributional Reinforcement Learning
by: Groom, Michael, et al.
Published: (2026)
by: Groom, Michael, et al.
Published: (2026)
Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+($λ$,$λ$))-GA
by: Nguyen, Tai, et al.
Published: (2025)
by: Nguyen, Tai, et al.
Published: (2025)
Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
by: Ma, Haitong, et al.
Published: (2024)
by: Ma, Haitong, et al.
Published: (2024)
Safe Reinforcement Learning-Based Vibration Control: Overcoming Training Risks with LQR Guidance
by: Thorat, Rohan Vitthal, et al.
Published: (2025)
by: Thorat, Rohan Vitthal, et al.
Published: (2025)
Flow-based Policy With Distributional Reinforcement Learning in Trajectory Optimization
by: Hao, Ruijie, et al.
Published: (2026)
by: Hao, Ruijie, et al.
Published: (2026)
FlowCritic: Bridging Value Estimation with Flow Matching in Reinforcement Learning
by: Zhong, Shan, et al.
Published: (2025)
by: Zhong, Shan, et al.
Published: (2025)
Discrete Flow Matching for Offline-to-Online Reinforcement Learning
by: Khan, Fairoz Nower, et al.
Published: (2026)
by: Khan, Fairoz Nower, et al.
Published: (2026)
Cyclical Entropy Eruption: Entropy Dynamics in Agent Reinforcement Learning
by: Li, Wendi, et al.
Published: (2026)
by: Li, Wendi, et al.
Published: (2026)
ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
by: Li, Ziniu, et al.
Published: (2023)
by: Li, Ziniu, et al.
Published: (2023)
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
by: Chao, Chen-Hao, et al.
Published: (2024)
by: Chao, Chen-Hao, et al.
Published: (2024)
Flow Matching Policy Optimization with Mirror Descent and Entropy Constraints
by: Gao, Ting, et al.
Published: (2026)
by: Gao, Ting, et al.
Published: (2026)
Maximum Entropy Heterogeneous-Agent Reinforcement Learning
by: Liu, Jiarong, et al.
Published: (2023)
by: Liu, Jiarong, et al.
Published: (2023)
Reflected Flow Matching
by: Xie, Tianyu, et al.
Published: (2024)
by: Xie, Tianyu, et al.
Published: (2024)
Similar Items
-
Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
by: Zhang, Yuyang, et al.
Published: (2026) -
Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
by: Li, Zeqiao, et al.
Published: (2026) -
Evolving Diffusion and Flow Matching Policies for Online Reinforcement Learning
by: Zhang, Chubin, et al.
Published: (2025) -
A Model-Based Approach to Imitation Learning through Multi-Step Predictions
by: Balim, Haldun, et al.
Published: (2025) -
Efficient Online Reinforcement Learning for Diffusion Policy
by: Ma, Haitong, et al.
Published: (2025)