Graph-Reweighted Behavior Cloning with Human Interventions for Precise Robotic Manipulation
cs.RO
Submitted: 2026-10-14
Updated: 2026-10-14
Comments: Accepted at CoRL 2026. 25 pages, 16 figures, including appendix. Project page: https://gr-bc.github.io/
Project page: https://gr-bc.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- OpenVLA: An Open-Source Vision-Language-Action Model
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- Igniting VLMs toward the Embodied Space
- A Pragmatic VLA Foundation Model
- PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations
- Steering Vision-Language-Action Models as Anti-Exploration: A Test-Time Scaling Approach
- NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces
- Offline Imitation Learning Through Graph Search and Retrieval
- ARM: Advantage Reward Modeling for Long-Horizon Manipulation
- Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments
- SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation
- ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation
- Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
- RoboReward: General-Purpose Vision-Language Reward Models for Robotics
- Robo-Dopamine: General Process Reward Modeling for High-Precision Robotic Manipulation
- TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics
- Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models
- DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
- Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
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