From the 1 of 21 linked papers with an AI index.
21 papers
DLAM: Distributional Latent Actions with Temporal Constraints
Zuojin Tang, Feifan Luo, Haoyun Liu +10
The paper introduces DLAM, a distributional latent-action model that encodes video transitions as diagonal Gaussians with temporal constraints, improving reconstruction consistency…
ABot-M0.5: Unified Mobility-and-Manipulation World Action Model
Ronghan Chen, Yandan Yang, Zuojin Tang +18
Mobile manipulation is a key capability for general-purpose robots, yet remains challenging for current embodied learning methods. VLA policies are typically reactive and lack expl…
Neural Implicit Action Fields: From Discrete Waypoints to Continuous Functions for Vision-Language-Action Models
Haoyun Liu, Jianzhuang Zhao, Xinyuan Chang +11
Despite the rapid progress of vision-language-action (VLA) models, the prevailing practice of predicting action chunks as discrete waypoints remains structurally misaligned with th…
ALAM: Algebraically Consistent Latent Action Model for Vision-Language-Action Models
Zuojin Tang, Haoyun Liu, Xinyuan Chang +11
Vision-language-action (VLA) models remain constrained by the scarcity of action-labeled robot data, whereas action-free videos provide abundant evidence of how the physical world…
Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
Junjin Xiao, Dongyang Li, Yandan Yang +9
This paper tackles spatial perception and manipulation challenges in Vision-Language-Action (VLA) models. To address depth ambiguity from monocular input, we leverage a pre-trained…
World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training
Junjin Xiao, Yandan Yang, Xinyuan Chang +5
Vision-Language-Action (VLA) models trained via imitation learning suffer from significant performance degradation in data-scarce scenarios due to their reliance on large-scale dem…