A vision-language-action model trained with supervised and reinforcement learning tracks endoscopic targets and simple objects on a robotic endoscope.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
EndoVLA: Dual-Phase Vision-Language-Action Model for Autonomous Tracking in Endoscopy
A vision-language-action model trained with supervised and reinforcement learning tracks endoscopic targets and simple objects on a robotic endoscope.