Image de couverture de livre

World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Xiao, Junjin, Yang, Yandan, Chang, Xinyuan, Chen, Ronghan, Xiong, Feng, Xu, Mu, Zheng, Wei-Shi, Zhang, Qing
Format:	Preprint
Publié:	2025
Sujets:	Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

ABot-PhysWorld: Interactive World Foundation Model for Robotic Manipulation with Physics Alignment
par: Chen, Yuzhi, et autres
Publié: (2026)

ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
par: Yang, Yandan, et autres
Publié: (2026)

Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
par: Xiao, Junjin, et autres
Publié: (2026)

DriveEnv-NeRF: Exploration of A NeRF-Based Autonomous Driving Environment for Real-World Performance Validation
par: Shen, Mu-Yi, et autres
Publié: (2024)

AtomVLA: Scalable Post-Training for Robotic Manipulation via Predictive Latent World Models
par: Sun, Xiaoquan, et autres
Publié: (2026)

WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL
par: Jiang, Zhennan, et autres
Publié: (2026)

World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy
par: Liu, Xiaokang, et autres
Publié: (2026)

WorldVLA: Towards Autoregressive Action World Model
par: Cen, Jun, et autres
Publié: (2025)

VLA Model Post-Training via Action-Chunked PPO and Self Behavior Cloning
par: Wang, Si-Cheng, et autres
Publié: (2025)

Seeing Space and Motion: Enhancing Latent Actions with Geometric and Dynamic Awareness for Vision-Language-Action Models
par: Cai, Zhejia, et autres
Publié: (2025)

Uni-World VLA: Interleaved World Modeling and Planning for Autonomous Driving
par: Liu, Qiqi, et autres
Publié: (2026)

Learning from Mistakes: Post-Training for Driving VLA with Takeover Data
par: Gao, Yinfeng, et autres
Publié: (2026)

BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models
par: Chen, Zhongxi, et autres
Publié: (2026)

Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training
par: Li, Yaxuan, et autres
Publié: (2026)

Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
par: Xiang, Tian-Yu, et autres
Publié: (2025)

Can VLA Models Learn from Real-World Data Continually without Forgetting?
par: Zhu, Jiarun, et autres
Publié: (2026)

WorldGym: World Model as An Environment for Policy Evaluation
par: Quevedo, Julian, et autres
Publié: (2025)

Galaxea Open-World Dataset and G0 Dual-System VLA Model
par: Jiang, Tao, et autres
Publié: (2025)

PokeVLA: Empowering Pocket-Sized Vision-Language-Action Model with Comprehensive World Knowledge Guidance
par: Zheng, Yupeng, et autres
Publié: (2026)

Long-Term Memory for VLA-based Agents in Open-World Task Execution
par: Huang, Xu, et autres
Publié: (2026)

RynnVLA-002: A Unified Vision-Language-Action and World Model
par: Cen, Jun, et autres
Publié: (2025)

IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model
par: Jiang, Anqing, et autres
Publié: (2025)

ALAM: Algebraically Consistent Latent Action Model for Vision-Language-Action Models
par: Tang, Zuojin, et autres
Publié: (2026)

EVOLVE-VLA: Test-Time Training from Environment Feedback for Vision-Language-Action Models
par: Bai, Zechen, et autres
Publié: (2025)

Goal-VLA: Image-Generative VLMs as Object-Centric World Models Empowering Zero-shot Robot Manipulation
par: Chen, Haonan, et autres
Publié: (2025)

VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model
par: Li, Wenhao, et autres
Publié: (2026)

Real-to-Sim Grasp: Rethinking the Gap between Simulation and Real World in Grasp Detection
par: Cai, Jia-Feng, et autres
Publié: (2024)

TriVLA: A Triple-System-Based Unified Vision-Language-Action Model with Episodic World Modeling for General Robot Control
par: Liu, Zhenyang, et autres
Publié: (2025)

World-Gymnast: Training Robots with Reinforcement Learning in a World Model
par: Sharma, Ansh Kumar, et autres
Publié: (2026)

PointVLA: Injecting the 3D World into Vision-Language-Action Models
par: Li, Chengmeng, et autres
Publié: (2025)

JailWAM: Jailbreaking World Action Models in Robot Control
par: Liu, Hanqing, et autres
Publié: (2026)

LogicEnvGen: Task-Logic Driven Generation of Diverse Simulated Environments for Embodied AI
par: Wang, Jianan, et autres
Publié: (2026)

DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving
par: jia, Feiyang, et autres
Publié: (2026)

RobustVLA: Robustness-Aware Reinforcement Post-Training for Vision-Language-Action Models
par: Zhang, Hongyin, et autres
Publié: (2025)

Balancing Signal and Variance: Adaptive Offline RL Post-Training for VLA Flow Models
par: Zhang, Hongyin, et autres
Publié: (2025)

GeoPredict: Leveraging Predictive Kinematics and 3D Gaussian Geometry for Precise VLA Manipulation
par: Qian, Jingjing, et autres
Publié: (2025)

ST4VLA: Spatially Guided Training for Vision-Language-Action Models
par: Ye, Jinhui, et autres
Publié: (2026)

FlyCo: Foundation Model-Empowered Drones for Autonomous 3D Structure Scanning in Open-World Environments
par: Feng, Chen, et autres
Publié: (2026)

Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models
par: Shi, Liangzhi, et autres
Publié: (2026)

EnvBridge: Bridging Diverse Environments with Cross-Environment Knowledge Transfer for Embodied AI
par: Kagaya, Tomoyuki, et autres
Publié: (2024)