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cs.LG2026
LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning
Xunkai Li, Zekai Chen, Zhengyu Wu +6
Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to multimodal-attributed graphs. This…
cs.LG2026
Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach
Sicheng Liu, Xunkai Li, Daohan Su +4
Graph Foundation Models (GFMs) have achieved remarkable success in generalizing across diverse domains. However, they mainly focus on Text-Attributed Graphs (TAGs), leaving Multimo…
cs.LG2026
DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis
Ru Zhang, Xunkai Li, Yaxin Deng +7
Recently, data-centric AI methodology has been a dominant paradigm in single-cell transcriptomics analysis, which treats data representation rather than model complexity as the fun…