Steertuning Policies from a Few Human Videos
cs.RO, cs.AI
Submitted: 2026-10-13
Updated: 2026-10-13
Project page: https://steertuning.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- DexWild: Dexterous Human Interactions for In-the-Wild Robot Policies
- In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data
- EgoZero: Robot Learning from Smart Glasses
- Dexterity from Smart Lenses: Multi-Fingered Robot Manipulation with In-the-Wild Human Demonstrations
- Point Policy: Unifying Observations and Actions with Key Points for Robot Manipulation
- OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation
- Holo-Dex: Teaching Dexterity with Immersive Mixed Reality
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Octo: An Open-Source Generalist Robot Policy
- LoRA: Low-Rank Adaptation of Large Language Models
- DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policy
- DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation
- Human Universal Grasping
- OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics
- Gemini Robotics: Bringing AI into the Physical World
- OpenVLA: An Open-Source Vision-Language-Action Model
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Steering Your Diffusion Policy with Latent Space Reinforcement Learning
- Classifier-Free Diffusion Guidance
- Planning with Diffusion for Flexible Behavior Synthesis
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