9 papers indexed
Shuai Wang, Shen Wang, Qiang Wang, Muguo Du, Donghai Shi, Chenyu Wang, et al.
Developing autonomous hydraulic excavators is constrained by limited access to physical machines and the high cost of real-world experimentation. This paper proposes a simulation-to-real framework for learning a system-level digital surrogate using Long Short-Term Memory (LSTM) n…
Zhihan Jiang, Meng Li, Shenghao Liu, Keran Li, Ruiben Zhou, Wei Wang, et al.
Deploying large language models (LLMs) as personal assistants on mobile devices demands privacy, low latency, and offline availability, yet the computational cost of giant models clashes with strict edge-hardware budgets. We argue that this tension cannot be resolved by model com…
Zuzhi Yang, Bingtao Ma, Shuai Wang, Mounir Kaaniche, Ziwei Li, Zhiming Cheng, et al.
Category-level object pose estimation is a crucial yet challenging task in both academia and industry, and has achieved remarkable success by leveraging keypoint-based correspondence paradigms. However, most existing methods increasingly rely on stronger feature learning while ov…
Gengyang Xu, Dongwei Xiao, Hengcheng Zhu, Yiteng Peng, Wei Meng, Shuai Wang, et al.
As 3D software proliferates, software artifacts now extend beyond code and 2D user interfaces to include 3D assets. Among these assets, collision meshes are critical as they define the geometry used by physics engines for collision detection and physical interaction. Although exi…
Qibing Bai, Shuai Wang, Yuhan Du, Bohan Li, Yannan Wang, Haizhou Li
Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity. The current techniques either require naturally recorded parallel L1-L2 speech for training, or suffer from quality degradation when supervised…
Ling Xu, Chuyu Han, Borui Li, Hao Wu, Shiqi Jiang, Ting Cao, et al.
Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model-specific Python stacks, backend assumptions, and robot-side glue code, especially on heterogeneous edge devices. Existing infer…
Xuanyu Chen, Nan Yang, Shuai Wang, Dong Yuan
Recent research has introduced distributed self-supervised learning (D-SSL) approaches to leverage vast amounts of unlabeled decentralized data. However, D-SSL faces the critical challenge of data heterogeneity, and there is limited theoretical understanding of how different D-SS…
Li Jin, Jian Huang, Junde Lu, Shuai Wang, Hao Sheng, Jie Wu
Light Field Super-Resolution (LFSR) necessitates accurate modeling of spatial-angular correlations while preserving intrinsic 4D ray coherence. However, maintaining such high-dimensional consistency remains challenging, primarily due to two inherent limitations in prevailing mode…
Yuqing Yang, Qi Zhu, Zhen Han, Boran Han, Zhengyuan Shen, Shuai Wang, et al.
While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e., incorrectly citing or omitting table values, despite understanding the table structure. Beyond final-answer accuracy, DREs directly compromise the correctness and…