2 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Senqiao Yang, Chengyao Wang, Yuxin Chen +13
Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodie…
StarVLA-: Reducing Complexity in Vision-Language-Action Systems
Jinhui Ye, Ning Gao, Senqiao Yang +7
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landscape remains highly fragmented…
VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models
Zixuan Wang, Yuxin Chen, Yuqi Liu +6
Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to control signals. This "black-box" mapping forces a single forward pass…
DaDu-E: Rethinking the Role of Large Language Model in Robotic Computing Pipeline
Wenhao Sun, Sai Hou, Zixuan Wang +6
Performing complex tasks in open environments remains challenging for robots, even when using large language models (LLMs) as the core planner. Many LLM-based planners are ineffici…
KARMA: Augmenting Embodied AI Agents with Long-and-short Term Memory Systems
Zixuan Wang, Bo Yu, Junzhe Zhao +6
Embodied AI agents responsible for executing interconnected, long-sequence household tasks often face difficulties with in-context memory, leading to inefficiencies and errors in t…