CARE: Experience-Guided Atomic Corrective Execution for Vision-Language-Action Policies
cs.RO
Submitted: 2026-09-21
Updated: 2026-09-21
Code: https://github.com/xiaojunlan/care
Terminology
Sources
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- FAST: Efficient Action Tokenization for Vision-Language-Action Models
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- Affordance Field Intervention: Enabling VLAs to Escape Memory Traps in Robotic Manipulation
- FailSafe: Reasoning and Recovery from Failures in Vision-Language-Action Models
- Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies
- Yell At Your Robot: Improving On-the-Fly from Language Corrections
- AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation
- Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning
- FPC-VLA: A Vision-Language-Action Framework with a Supervisor for Failure Prediction and Correction
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
- RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
- DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control
- HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model
- Octo: An Open-Source Generalist Robot Policy
- FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization
- UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
- OpenVLA: An Open-Source Vision-Language-Action Model
- ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
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