A 12B-parameter VLM learns to synthesize executable Behavior Tree policies from multimodal inputs via synthetic neuro-symbolic supervision, achieving zero-shot real-world transfer on robotic manipulators.
Deep object pose estimation for semantic robotic grasping of household objects
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision
A 12B-parameter VLM learns to synthesize executable Behavior Tree policies from multimodal inputs via synthetic neuro-symbolic supervision, achieving zero-shot real-world transfer on robotic manipulators.