LLaDA-VLA applies a masked diffusion vision-language model to robot control with localized action-token classification and hierarchical decoding, achieving SOTA success rates on SimplerEnv, CALVIN, and real-robot tasks.
Open x-embodiment: Robotic learning datasets and rt-x models
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
LLaDA-VLA: Vision Language Diffusion Action Models
LLaDA-VLA applies a masked diffusion vision-language model to robot control with localized action-token classification and hierarchical decoding, achieving SOTA success rates on SimplerEnv, CALVIN, and real-robot tasks.