4 papers indexed
Yunan Zhang, Yang Fan, Heng Li, Xiangping Wu, Qingcai Chen
Continual Learning for Named Entity Recognition (CLNER) enable models to incrementally learn new entity types without forgetting previously acquired ones. However, existing methods suffer from catastrophic forgetting and insufficient exploitation of shared information across task…
Wun Lam Yeung, Wenjun Liu, Yui Cheung Yu, Zhengyan Lambo Qin, Qijin She, Heng Li, et al.
Bimanual object reorientation - picking an object, handing it over between two arms, and placing it in a desired target pose - is valuable when direct placement from the initial grasp is infeasible due to collisions, kinematic constraints, or poor final orientation. However, achi…
Junyuan Deng, Heng Li, Kejie Qiu, Lingteng Qiu, Rui Peng, Weichao Shen, et al.
Recent 3D geometric foundation models, such as VGGT, provide robust feed-forward 3D reconstruction by directly predicting camera poses and 3D scene points from input images. However, their results remain inaccurate, and scaling them to long sequences or large unordered image sets…
Longyu Chen, Heng Li, Wei Yang, Manqi Zhao, Dongsheng Jiang
Embodied World Models (EWMs) have emerged as a scalable and risk-free paradigm for advancing embodied intelligence, enabling the safety-critical evaluation of Vision-Language-Action systems. However, their reliability as evaluation benchmarks and foundational simulators is often…