Saved in:
| Main Authors: | Sun, Xiaolin, Liu, Feidi, Ding, Zhengming, Zheng, ZiZhan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.07701 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
by: Zheng, Yinan, et al.
Published: (2024)
by: Zheng, Yinan, et al.
Published: (2024)
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
by: Liu, Qianmei, et al.
Published: (2024)
by: Liu, Qianmei, et al.
Published: (2024)
Adversarial Diffusion for Robust Reinforcement Learning
by: Foffano, Daniele, et al.
Published: (2025)
by: Foffano, Daniele, et al.
Published: (2025)
Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
by: Luu, Tung M., et al.
Published: (2024)
by: Luu, Tung M., et al.
Published: (2024)
Towards Robust Deep Reinforcement Learning against Environmental State Perturbation
by: Wang, Chenxu, et al.
Published: (2025)
by: Wang, Chenxu, et al.
Published: (2025)
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
by: Liang, Yongyuan, et al.
Published: (2023)
by: Liang, Yongyuan, et al.
Published: (2023)
Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
by: Sun, Xiaolin, et al.
Published: (2024)
by: Sun, Xiaolin, et al.
Published: (2024)
Stabilizing Reinforcement Learning for Diffusion Language Models
by: Zhong, Jianyuan, et al.
Published: (2026)
by: Zhong, Jianyuan, et al.
Published: (2026)
Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies
by: Fan, Junchao, et al.
Published: (2025)
by: Fan, Junchao, et al.
Published: (2025)
Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
by: Mao, Liyuan, et al.
Published: (2024)
by: Mao, Liyuan, et al.
Published: (2024)
State-Aware Perturbation Optimization for Robust Deep Reinforcement Learning
by: Zhang, Zongyuan, et al.
Published: (2025)
by: Zhang, Zongyuan, et al.
Published: (2025)
Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation
by: Zhou, Zhijian, et al.
Published: (2025)
by: Zhou, Zhijian, et al.
Published: (2025)
Enhancing Reinforcement Learning Fine-Tuning with an Online Refiner
by: Ma, Hao, et al.
Published: (2026)
by: Ma, Hao, et al.
Published: (2026)
Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport
by: Sun, Mingyang, et al.
Published: (2025)
by: Sun, Mingyang, et al.
Published: (2025)
Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach
by: Fan, Junchao, et al.
Published: (2025)
by: Fan, Junchao, et al.
Published: (2025)
Advantage-Guided Diffusion for Model-Based Reinforcement Learning
by: Foffano, Daniele, et al.
Published: (2026)
by: Foffano, Daniele, et al.
Published: (2026)
Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning
by: Ding, Zihan, et al.
Published: (2024)
by: Ding, Zihan, et al.
Published: (2024)
Adversarial Attacks on Reinforcement Learning-based Medical Questionnaire Systems: Input-level Perturbation Strategies and Medical Constraint Validation
by: Liu, Peizhuo
Published: (2025)
by: Liu, Peizhuo
Published: (2025)
GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
by: Tang, Xiaohang, et al.
Published: (2026)
by: Tang, Xiaohang, et al.
Published: (2026)
CausalGDP: Causality-Guided Diffusion Policies for Reinforcement Learning
by: Xiao, Xiaofeng, et al.
Published: (2026)
by: Xiao, Xiaofeng, et al.
Published: (2026)
PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling
by: Yuan, Xinyu, et al.
Published: (2026)
by: Yuan, Xinyu, et al.
Published: (2026)
State-Novelty Guided Action Persistence in Deep Reinforcement Learning
by: Hu, Jianshu, et al.
Published: (2024)
by: Hu, Jianshu, et al.
Published: (2024)
Towards Robust Zero-Shot Reinforcement Learning
by: Zheng, Kexin, et al.
Published: (2025)
by: Zheng, Kexin, et al.
Published: (2025)
Diffusion-Reward Adversarial Imitation Learning
by: Lai, Chun-Mao, et al.
Published: (2024)
by: Lai, Chun-Mao, et al.
Published: (2024)
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
by: Liu, Zeyuan, et al.
Published: (2025)
by: Liu, Zeyuan, et al.
Published: (2025)
How Worst-Case Are Adversarial Attacks? Linking Adversarial and Perturbation Robustness
by: Rossolini, Giulio
Published: (2026)
by: Rossolini, Giulio
Published: (2026)
A Neural Rejection System Against Universal Adversarial Perturbations in Radio Signal Classification
by: Zhang, Lu, et al.
Published: (2025)
by: Zhang, Lu, et al.
Published: (2025)
Adversarial Environment Design via Regret-Guided Diffusion Models
by: Chung, Hojun, et al.
Published: (2024)
by: Chung, Hojun, et al.
Published: (2024)
Bidirectional-Reachable Hierarchical Reinforcement Learning with Mutually Responsive Policies
by: Luo, Yu, et al.
Published: (2024)
by: Luo, Yu, et al.
Published: (2024)
Scale-free Adversarial Reinforcement Learning
by: Chen, Mingyu, et al.
Published: (2024)
by: Chen, Mingyu, et al.
Published: (2024)
Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)
by: Yang, Jinluan, et al.
Published: (2025)
Generating Universal Adversarial Perturbations for Quantum Classifiers
by: Anil, Gautham, et al.
Published: (2024)
by: Anil, Gautham, et al.
Published: (2024)
DFKI-Speech System for WildSpoof Challenge: A robust framework for SASV In-the-Wild
by: Das, Arnab, et al.
Published: (2026)
by: Das, Arnab, et al.
Published: (2026)
Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks
by: Fang, Junyuan, et al.
Published: (2025)
by: Fang, Junyuan, et al.
Published: (2025)
Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
by: Jin, Luozhijie, et al.
Published: (2025)
by: Jin, Luozhijie, et al.
Published: (2025)
POLO: Preference-Guided Multi-Turn Reinforcement Learning for Lead Optimization
by: Wang, Ziqing, et al.
Published: (2025)
by: Wang, Ziqing, et al.
Published: (2025)
DLPO: Diffusion Model Loss-Guided Reinforcement Learning for Fine-Tuning Text-to-Speech Diffusion Models
by: Chen, Jingyi, et al.
Published: (2024)
by: Chen, Jingyi, et al.
Published: (2024)
CAMEL: Continuous Action Masking Enabled by Large Language Models for Reinforcement Learning
by: Zhao, Yanxiao, et al.
Published: (2025)
by: Zhao, Yanxiao, et al.
Published: (2025)
Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)
by: Duan, Tianyang, et al.
Published: (2025)
Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees
by: Queeney, James, et al.
Published: (2023)
by: Queeney, James, et al.
Published: (2023)
Similar Items
-
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
by: Zheng, Yinan, et al.
Published: (2024) -
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
by: Liu, Qianmei, et al.
Published: (2024) -
Adversarial Diffusion for Robust Reinforcement Learning
by: Foffano, Daniele, et al.
Published: (2025) -
Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
by: Luu, Tung M., et al.
Published: (2024) -
Towards Robust Deep Reinforcement Learning against Environmental State Perturbation
by: Wang, Chenxu, et al.
Published: (2025)