MIM-VLA: Learning Physical Interaction Representations from Gripper Motor Feedback
cs.RO
Submitted: 2026-10-06
Updated: 2026-10-06
Comments: 9 pages, 7 figures. Jaeyoung Lee and Jiyeon Koo contributed equally
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- OpenVLA: An Open-Source Vision-Language-Action Model
- SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
- Tactile-VLA: Unlocking Vision-Language-Action Model's Physical Knowledge for Tactile Generalization
- Bi-ACT: Bilateral Control-Based Imitation Learning via Action Chunking with Transformer
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models
- VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation
- Qwen2.5-VL Technical Report
- SmolVLM: Redefining small and efficient multimodal models
- RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models
- When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
- Layer Normalization
- Gaussian Error Linear Units (GELUs)
- SAM 2: Segment Anything in Images and Videos
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