no code implementations • 17 Dec 2024 • Wenyu Zhang, Wei En Ng, Lixin Ma, Yuwen Wang, Jungqi Zhao, Boyang Li, Lu Wang
Current vision-language models may incorporate single-dimensional spatial cues, such as depth, object boundary, and basic spatial directions (e. g. left, right, front, back), yet often lack the multi-dimensional spatial reasoning necessary for human-like understanding and real-world applications.
1 code implementation • 2 Jul 2024 • Yuwen Wang, Shunyu Liu, Tongya Zheng, KaiXuan Chen, Mingli Song
Graph Neural Networks (GNNs) have emerged as a prominent framework for graph mining, leading to significant advances across various domains.
1 code implementation • 25 Jun 2024 • Feiyang Xu, Shunyu Liu, Yunpeng Qing, Yihe Zhou, Yuwen Wang, Mingli Song
In this paper, we propose a novel temporal prototype-aware learning method, abbreviated as TPA, to learn time-adaptive AVC under short-term training trajectories.
1 code implementation • 5 Aug 2023 • Yuwen Wang, Shunyu Liu, KaiXuan Chen, Tongtian Zhu, Ji Qiao, Mengjie Shi, Yuanyu Wan, Mingli Song
Graph Lottery Ticket (GLT), a combination of core subgraph and sparse subnetwork, has been proposed to mitigate the computational cost of deep Graph Neural Networks (GNNs) on large input graphs while preserving original performance.