The authors evaluated RoboICL on 30 RoboDojo manipulation tasks, using no demonstration for Open tasks and one demonstration for the other categories.
Structured context helps a general vision model control robots better
RoboICL combines demonstrations with anchored interaction history to improve manipulation without updating the underlying model.
Big Tech
Fangcheng Liu · Yeqing Shen · Anda Cheng · Weishi Mi · Chao Tang · Chenyuan Liu · +4 more
Samsung Robotics eXperience · Shanghai Jiao Tong University · Samsung Research
Research Digest··2 min read
Liu and colleagues built an inference-time control framework around GPT-6 Astra, organizing demonstrations, actions, and execution feedback into a shared context format.
Why this paper
From Samsung Robotics eXperience and 2 others · Released code
In one line
RoboICL uses in-context learning to improve GPT-6 Astra robot control by 20-27 progress-score points on RoboDojo tasks.
What it released
Code
What we could check
- ✓Code link in the paper (github.com)
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ✓Reports numbers on named benchmarks (3 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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