Sim-trained ZAP robot policy hits 96.7% on real tasks
A 27B vision-language model fine-tuned only in simulation matches GPT-6 Astra and beats MolmoAct2's 33.3% in the same harness.
48
Product
Franka
- Mentions · 7d0
- Mentions · 30d1
- All mentions7
- First seenSep 18, 2026
- Last mentioned16d ago
Timeline
7 articles · newest firstRoboCoach: World Models as Active Coaches for Compositional Robot Skills
RoboCoach uses a world model to target robot skill demos, lifting Franka success from 13.3% to 75%.
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Game-Guided Skill Discovery through Self-Play for Playable Agent Control
GGSD uses game self-play to learn a small set of human-playable motor skills for embodied agents.
34
Real2Gym: Building Gyms from Videos, Bringing Skills to Robots
Real2Gym turns demonstration videos into physics gyms and transfers learned skills to a Franka robot.
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AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control
AD-WM improves counterfactual planning by preserving action information, raising hard-start success from 3.7% to 52%.
48
RAPID: Robot Agentic Programming from Demonstrations
RAPID turns one visual human demonstration into verified, reusable robot programs via an agentic coding loop.
42
Transferring the Intelligence of VLMs to Robotic Control
RoboDawn lets a VLM control robots via discrete commands, beating trained policies zero-shot and one-shot.
52
Appears with
- GPT-6 Astraai model · 2
- RoboTwinproduct · 1
- ZAPai model · 1
- Unitreevendor · 1
- LeWMai model · 1
- RoboDawnproduct · 1
- V-JEPA 2ai model · 1
- pi0.5ai model · 1
- DROIDproduct · 1
- COACHWORLDai model · 1
- AgileXproduct · 1
- RoboDojoproduct · 1
- OGBenchproduct · 1
- LIBERO-Proproduct · 1
- AD-WMai model · 1
- Unitree G1product · 1
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