9 citations · 11 across the 8 of their papers we have counts for
9 papers
EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action
Hao Wang, Jiajun Wen, Jingzhi Liu +21
Vision-language-action (VLA) policies emphasize semantic understanding, whereas world-action models (WAMs) learn predictive representations of environment dynamics. Systems that ex…
A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model
Kaidong Zhang, Jian Zhang, Rongtao Xu +20
Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often constrained by cost: billion-scal…
EchoVLA: Robotic Vision-Language-Action Model with Synergistic Declarative Memory for Mobile Manipulation
Min Lin, Xiwen Liang, Bingqian Lin +12
Recent progress in Vision-Language-Action (VLA) models has enabled embodied agents to interpret multimodal instructions and perform complex tasks. However, existing VLAs are mostly…
AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis
Shidan He, Lei Liu, Xiujun Shu +3
Anomaly synthesis is a crucial approach to augment abnormal data for advancing anomaly inspection. Based on the knowledge from the large-scale pre-training, existing text-to-image…
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation
Youpeng Wen, Junfan Lin, Yi Zhu +4
Recent advancements utilizing large-scale video data for learning video generation models demonstrate significant potential in understanding complex physical dynamics. It suggests…
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label Classification
Gexin Huang, Chenfei Wu, Mingjie Li +6
Predicting genetic mutations from whole slide images is indispensable for cancer diagnosis. However, existing work training multiple binary classification models faces two challeng…
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training
Xinchi Deng, Han Shi, Runhui Huang +7
Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, on…
Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining
Bingqian Lin, Zicong Chen, Mingjie Li +13
Medical artificial general intelligence (MAGI) enables one foundation model to solve different medical tasks, which is very practical in the medical domain. It can significantly re…
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
Binbin Yang, Xinchi Deng, Han Shi +6
Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual class…