12 citations · 16 across the 23 of their papers we have counts for
11 papers · 1 filter
Language-Forcing: Advancing Humanoid Loco-Manipulation via Semantic Alignment of Whole-Body World Action Models
Yanjun Li, Jiarui Ye, Weiyu Guo +7
World Action Models (WAMs) jointly predict robot actions and future observations. However, their visual prediction objectives do not explicitly distinguish task-relevant transition…
Unsupervised Post-Training of Foundation Models: A Survey
Yijie Xu, Qianyi Cai, Huizai Yao +9
Foundation-model post-training usually relies on human labels, preference data, stronger teachers, or executable verifiers. We study Unsupervised Post-Training (UPT): update-bearin…
The Geometry of Flow-Matching Uncertainty: A Cost-free Uncertainty Proxy and Its Application in Flow-based VLA Failure Detection
Ziyang Rao, Yiren Zhao, Weiyu Guo +3
Flow matching (FM) has become a popular action head paradigm for modern embodied models. However, as a conditional generative model, it does not explicitly expose its inherent unce…
Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies
Shaoguang Wang, Weiyu Guo, Rushi Dai +3
Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We present a target-and-control audit o…
How Should Vision-Language-Action Models Use Proprioceptive State?
Yiren Zhao, Ziyang Chen, Ziyang Rao +5
Recent Vision-Language-Action (VLA) models almost universally take robot proprioceptive state as input, yet wire it in incompatible ways -- serialized into text prompts, projected…
Source-Lifted Flow Matching for Intervenable Multimodal Imitation
He Zhang, Ying Sun, Pengteng Li +7
Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity is largely passive: repeated sa…
Event-VLA: Action-Conditioned Event Fusion for Robust Vision-Language-Action Model
Jiaxin Liu, Xun Xu, Zhenhao Zhang +5
Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable indoor settings, while real-…
PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models
Ziyang Chen, Shaoguang Wang, Weiyu Guo +5
Vision-Language-Action (VLA) models have achieved remarkable success in language-conditioned robotic manipulation. However, deploying these models in open-ended environments requir…
Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
Pengteng Li, Weiyu Guo, He Zhang +4
We introduce SOMA, the Spatial Memory framework for Out-of-Vision Manipulation in Vision-Language-Action (VLA) models. Most existing VLAs implicitly assume that task-relevant objec…
Where to Focus: Query-Modulated Multimodal Keyframe Selection for Long Video Understanding
Shaoguang Wang, Weiyu Guo, Ziyang Chen +2
Long video understanding remains a formidable challenge for Multimodal Large Language Models (MLLMs) due to the prohibitive cost of processing dense frame sequences. Prevailing key…
NeuroVLA: A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control
Weiyu Guo, He Zhang, Pengteng Li +7
Vision-language-action (VLA) models inherit powerful semantic representations from large language models, but carrying over their design priorities can leave the demands of physica…