CARF: Contrastive Attraction-Repulsion of Failure-Guided Flow Matching
cs.RO
Submitted: 2026-09-18
Updated: 2026-09-18
Project page: https://zhao-sq.github.io/carf/#
Terminology
Sources
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation
- DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation
- Rewind-IL: Online Failure Detection and State Respawning for Imitation Learning
- Multi-Camera View Scaling for Data-Efficient Robot Imitation Learning
- CRAFT: Video Diffusion for Bimanual Robot Data Generation
- Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference
- Using Non-Expert Data to Robustify Imitation Learning via Offline Reinforcement Learning
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
- FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning
- Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets
- Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
- DexCtrl: Towards Sim-to-Real Dexterity with Adaptive Controller Learning
- EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
- Seeing to Act, Prompting to Specify: A Bayesian Factorization of Vision Language Action Policy
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- Flow Matching for Generative Modeling
- DataMIL: Selecting Data for Robot Imitation Learning with Datamodels
- Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics
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- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving