PACER: Process-Aware VLA Policy Learning from Human Corrections for Robotic Disassembly
cs.RO
Submitted: 2026-10-13
Updated: 2026-10-13
Project page: https://pacer-corl.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- OpenVLA: An Open-Source Vision-Language-Action Model
- Octo: An Open-Source Generalist Robot Policy
- Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
- SELF-VLA: A Skill Enhanced Agentic Vision-Language-Action Framework for Contact-Rich Disassembly
- PAPO-VLA: Planning-Aware Policy Optimization for Vision-Language-Action Models
- SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
- $\pi_\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
- ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models
- Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
- Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
- Vision-Language-Action (VLA) Models: Concepts, Progress, Applications and Challenges
- Vision Language Action Models in Robotic Manipulation: A Systematic Review
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- Pure Vision Language Action (VLA) Models: A Comprehensive Survey
- Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
- AWAC: Accelerating Online Reinforcement Learning with Offline Datasets
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