4 citations · 8 across the 24 of their papers we have counts for
13 papers · 1 filter
Learning to Use Imagination: Progress-Conditioned Future Utilization for World Action Models
Yijie Zhu, Zitong Yu, Wei Li +4
World Action Models (WAMs) extend Vision-Language-Action (VLA) models by incorporating future visual dynamics into action generation. However, existing WAMs often utilize imagined…
LookAgain: Closed-Loop GUI Grounding with Visually Grounded Reflection
Renshan Zhang, Haoyang Meng, Yixiao He +3
Recent graphical user interface (GUI) grounders have significantly advanced single-shot accuracy on standard benchmarks, yet their performance degrades sharply on small targets, de…
From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
Bing Hu, Zaijing Li, Rui Shao +4
Vision-Language-Action (VLA) models often suffer from performance degradation under distribution shifts, as they struggle to learn generalized behavior representations across varyi…
HATS: Hardness-Aware Trajectory Synthesis for GUI Agents
Rui Shao, Ruize Gao, Bin Xie +5
Graphical user interface (GUI) agents powered by large vision-language models (VLMs) have shown remarkable potential in automating digital tasks, highlighting the need for high-qua…
SemanticVLA: Semantic-Aligned Sparsification and Enhancement for Efficient Robotic Manipulation
Wei Li, Renshan Zhang, Rui Shao +4
Vision-Language-Action (VLA) models have advanced in robotic manipulation, yet practical deployment remains hindered by two key limitations: 1) perceptual redundancy, where irrelev…
CogVLA: Cognition-Aligned Vision-Language-Action Model via Instruction-Driven Routing & Sparsification
Wei Li, Renshan Zhang, Rui Shao +2
Recent Vision-Language-Action (VLA) models built on pre-trained Vision-Language Models (VLMs) require extensive post-training, resulting in high computational overhead that limits…