Image de couverture de livre

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Simsir, Hikmet, Oguz, Ozgur S.
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Steering Your Diffusion Policy with Latent Space Reinforcement Learning
par: Wagenmaker, Andrew, et autres
Publié: (2025)

CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms
par: Yenicesu, Arda Sarp, et autres
Publié: (2024)

Latent Policy Steering through One-Step Flow Policies
par: Im, Hokyun, et autres
Publié: (2026)

Approximating Shapley Explanations in Reinforcement Learning
par: Beechey, Daniel, et autres
Publié: (2025)

Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
par: Kong, Lingkai, et autres
Publié: (2026)

GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning
par: Ding, Shutong, et autres
Publié: (2025)

Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
par: Sun, Xiaolin, et autres
Publié: (2025)

Latent Policy Steering with Embodiment-Agnostic Pretrained World Models
par: Wang, Yiqi, et autres
Publié: (2025)

Efficient Online Reinforcement Learning for Diffusion Policy
par: Ma, Haitong, et autres
Publié: (2025)

From Foresight to Forethought: VLM-In-the-Loop Policy Steering via Latent Alignment
par: Wu, Yilin, et autres
Publié: (2025)

Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
par: Koirala, Prajwal, et autres
Publié: (2024)

Latent Causal Diffusions for Single-Cell Perturbation Modeling
par: Lorch, Lars, et autres
Publié: (2026)

Symmetry-Aware Steering of Equivariant Diffusion Policies: Benefits and Limits
par: Park, Minwoo, et autres
Publié: (2025)

DiffPoGAN: Diffusion Policies with Generative Adversarial Networks for Offline Reinforcement Learning
par: Hu, Xuemin, et autres
Publié: (2024)

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning
par: Zhang, Hanping, et autres
Publié: (2025)

Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning
par: Kanazawa, Takuya, et autres
Publié: (2023)

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
par: Cheng, Xiaoyuan, et autres
Publié: (2026)

General and Efficient Steering of Unconditional Diffusion
par: Wang, Qingsong, et autres
Publié: (2026)

Maximum Entropy Reinforcement Learning with Diffusion Policy
par: Dong, Xiaoyi, et autres
Publié: (2025)

Evolving Diffusion and Flow Matching Policies for Online Reinforcement Learning
par: Zhang, Chubin, et autres
Publié: (2025)

Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
par: Alles, Marvin, et autres
Publié: (2024)

Curricula for Learning Robust Policies with Factored State Representations in Changing Environments
par: Panayiotou, Panayiotis, et autres
Publié: (2024)

Enhance the Safety in Reinforcement Learning by ADRC Lagrangian Methods
par: Zhang, Mingxu, et autres
Publié: (2026)

Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models
par: Nogueira, Brenda, et autres
Publié: (2026)

Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation
par: Sandilya, Ruchi, et autres
Publié: (2025)

Think Outside the Policy: In-Context Steered Policy Optimization
par: Huang, Hsiu-Yuan, et autres
Publié: (2025)

Creating Multi-Level Skill Hierarchies in Reinforcement Learning
par: Evans, Joshua B., et autres
Publié: (2023)

Locally Adaptive One-Class Classifier Fusion with Dynamic $\ell$p-Norm Constraints for Robust Anomaly Detection
par: Nourmohammadi, Sepehr, et autres
Publié: (2024)

Diffusion Policies for Risk-Averse Behavior Modeling in Offline Reinforcement Learning
par: Chen, Xiaocong, et autres
Publié: (2024)

A Theoretical Framework for Explaining Reinforcement Learning with Shapley Values
par: Beechey, Daniel, et autres
Publié: (2025)

Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
par: Jiang, Wenkang, et autres
Publié: (2026)

Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning
par: Ada, Suzan Ece, et autres
Publié: (2023)

Predictive Lagrangian Optimization for Constrained Reinforcement Learning
par: Zhang, Tianqi, et autres
Publié: (2025)

When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
par: Yuan, Jessie, et autres
Publié: (2026)

Latent Abstractions in Generative Diffusion Models
par: Franzese, Giulio, et autres
Publié: (2024)

Latent Schr{ö}dinger Bridge Diffusion Model for Generative Learning
par: Jiao, Yuling, et autres
Publié: (2024)

On the Perturbed States for Transformed Input-robust Reinforcement Learning
par: Luu, Tung M., et autres
Publié: (2024)

FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies
par: Gao, Chenxiao, et autres
Publié: (2026)

CODA: Coordination via On-Policy Diffusion for Multi-Agent Offline Reinforcement Learning
par: Hedman, Marcel, et autres
Publié: (2026)

Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
par: Ding, Shutong, et autres
Publié: (2024)