H4G, a framework that systematically reduces embedding radii using learnable block-diagonal scaling matrices and Möbius matrix multiplication, is proposed, demonstrating that faithful preservation of fine-grained structural details requires faithful preservation of fine-grained structural details in graph learning.
Heng Zhang, Jin Huang· Proceedings of the 32nd ACM...· 0 citations
FossilWriter represents the story world as a shared hypergraph and introduces a narrative layer that marks elements with developmental potential that grows during writing and serves as the single source of truth to ensure long-range consistency.
Heng Zhang, Yi-Hao Zhong, Lubin Gan et al.· Proceedings of the Thirty-Fi...· 0 citations
Text-attributed graphs are widely used across domains, offering rich opportunities for zero-shot learning via graph-text alignment. However, existing methods struggle with tasks requiring fine-grained pattern recognition, particularly on heterophilic graphs. Through empirical and theoretical analysis, we identify an ov...
Heng Zhang, Jin Huang· Proceedings of the 32nd ACM...· 0 citations
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