Recently, self-attention mechanisms have significantly advanced hyperspectral image classification (HSIC) by enabling effective modeling of long-range spatial–spectral dependencies. However, existing methods often suffer from blurred land-cover boundaries and insufficient discriminability between spectrally similar cla...
Zhen-Qiu Shu, Nan-Bo Liu, Ke-Xin Zeng et al.· IEEE Transactions on Geoscie...· 0 citations
A generative ACSA model that incorporates external knowledge is proposed, which retrieves fine-grained aspect-related terms from external knowledge bases and uses them to construct contrastive sentence pairs, generating enhanced aspect-related representations, thereby bridging the gap between the original text and pred...
Yan Xiang, Hao-Quan Luo, Yuan Qin et al.· ACM Transactions on Asian an...· 0 citations
This work proposes Hyperspherical Representation Equilibrium Shift (HyRES), a theoretically grounded, unsupervised framework that redefines node influence as a geometric displacement within the latent space, and leverages Linear Response Theory to derive a closed-form approximation of the global representation shift ca...
Yan-Tuan Xian, Chun-Ping Li, Hong-Bin Wang et al.· Proceedings of the 32nd ACM...· 0 citations
Identifying influential nodes in graph-structured data is a fundamental challenge. Traditional metrics ignore non-linear GNN semantics, while deep influence maximization methods require computationally expensive, simulation-based supervision. To bridge the gap between topological analysis and deep representation learni...
Yantuan Xian, Chunping Li, Hongbin Wang et al.· Proceedings of the 32nd ACM...· 0 citations
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