5 papers
TriWorldBench: A Tri-View Consistency Perspective on Embodied World Models
Xuanyi Liu, Haofeng Wang, Ruiqi Li +9
Embodied world models predict the outcomes of robot actions to support learning and planning. For robots equipped with head and wrist cameras, this requires complementary views: th…
RoboTwin-Phys: Do WAMs and VLAs Understand the Physical World?
Jiaqi Zhang, Feng Ye, Mingjia Yang +6
Physical-condition diversity is largely missing from current benchmarks for robot manipulation. While large-scale simulation benchmarks increasingly incorporate variations in objec…
When Does Execution Provenance Help Agent Memory Retrieval?
Yiqi Wang, Jinqian Ju, Jiaqi Zhang +4
A language agent's execution history can exceed its context window, requiring its memory system to retrieve complete supporting evidence under a hard token budget. Evidence may spa…
Graph Domain Adaptation Does Not End with Representation Learning
Ziqian Liu, Yongxue Xu, Enze Zhang +3
Graph domain adaptation (GDA) transfers knowledge from a labeled source graph to an unlabeled target graph under shifts in both node attributes and graph structure. Existing method…
IndustrialVLA-Bench: A Traceable Multi-Axis Evaluation of Open Robot Policy Models
Yiqi Wang, Zhifeng Rao, Jiaqi Zhang +7
Open robot policies increasingly follow two paradigms: vision-language-action models (VLAs) directly map observations and instructions to actions, whereas world-action models (WAMs…