SEES: A Self-Evolving Embodied System via Failure-Guided VLA Policy Adaptation
cs.RO
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- LHManip: A Dataset for Long-Horizon Language-Grounded Manipulation Tasks in Cluttered Tabletop Environments
- OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
- VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model
- Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
- RLDX-1 Technical Report
- RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks
- RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator
- Model-Based Runtime Monitoring with Interactive Imitation Learning
- CORAL: Scalable Multi-Task Robot Learning via LoRA Experts
- Human-in-the-Loop Imitation Learning using Remote Teleoperation
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splatting
- CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion
- Proximal Policy Optimization Algorithms
- Continually Evolving Skill Knowledge in Vision Language Action Model
- SeqVLA: Sequential Task Execution for Long-Horizon Manipulation with Completion-Aware Vision-Language-Action Model
- RLinf-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models
- ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
- ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning
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