SOURCE-LINKED INTELLIGENCE
Generalizing Manipulation Skills with a Local Coding Agent
Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstation. Most language-driven robots give the model a fixed action interface or a trained policy. Generalizing to a new task therefore means more engineering effort or more data collection, both time-consuming. We investigate whether a local open-weight vision-language model can control a robot and one-shot generalize to new variations of a task without new human programming or training. We let a local open-weight VLM, Qwen3.8-27B, drive a UR3e rob
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T14:32:17.000Z
First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.