robotics
The Robot Ran the Learned Code Without a Model in the Loop
Code-Only-as-Policy stores task and environment state explicitly, then shares one controllable library across episodes.
Summary
Code-Only-as-Policy stores task and environment state explicitly, then shares one controllable library across episodes.
Code-Only-as-Policy proposes removing the vision-language model from runtime decision-making after a coding agent has built an explicit state-tracking and control library. Camera images and proprioception update the represented robot, environment and task state; code then makes every decision. Across RoboDojo's 42 bimanual tasks, the reported library reached 70.24% success without a model at test time. The authors frame explicit state, controllable execution and reusable code as a medium for recursive improvement. They also state the boundary plainly: performance depends on how accurately the world state is represented and how robust the code logic is.
Why it matters
Code-Only-as-Policy stores task and environment state explicitly, then shares one controllable library across episodes.
Limits and context
- Code-Only-as-Policy proposes removing the vision-language model from runtime decision-making after a coding agent has built an explicit state-tracking and control library.
Key claims
Code-Only-as-Policy stores task and environment state explicitly, then shares one controllable library across episodes.
Qualification: Code-Only-as-Policy proposes removing the vision-language model from runtime decision-making after a coding agent has built an explicit state-tracking and control library.
Evidence: source-2026-10-11-011
Sources
- arXiv preprint 2610.12369, original v1arXiv / submitting research authors · primary research
Corrections
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