An adaptive geometric hypergraph encoder that projects entities into a product manifold and design a topology-aware gating mechanism to dynamically select optimal geometric spaces for each entity, and a role-aware Transformer equipped with role-specific projections and micro-structural bias injection to refine embeddin...
Ke-Jia Chen, Yu-Zhe Hu, Yu Ni et al.· Proceedings of the Thirty-Fi...· 0 citations
Entity alignment is a fundamental step for knowledge graph (KG) integration, yet the complex and heterogeneous structures of real-world KGs make accurate alignment particularly challenging. KG entity alignment faces two main challenges. First, representations learned in a single Euclidean or hyperbolic space struggle t...
Teng Fu, Gang Zhou, Chao Zhang· Journal of King Saud Univers...· 0 citations
This work introduces ICE (Interaction-aware Clifford Encoder), a multimodal graph foundation model built on a node-indexed Clifford latent field that ranks first in all 30 reported supervised and few-shot comparisons.
Xun-Kai Li, Xu Wang, Yin-Lin Zhu et al.· 0 citations
ReCoG (Reciprocal Co-Evolution for Multimodal Graph Learning) is proposed, a new learning paradigm that tightly couples graph structure learning and multimodal representation learning through end-to-end reciprocal interaction and yields greater expressiveness than decoupled or two-stage formulations.
BaryBind is presented, which aims to transport the specific modality towards the Wasserstein barycenter (WB) optimized across all modalities and introduces a volumetric alignment objective to establish a unified semantic space around the WB embedding.
Xiao-Le Tang, Jia-Yi Xu, Xiang Gu et al.· 2 citations
A Semantic Manifold-Aware Similarity Learning (SMSL) framework, where the term "semantic manifold" is used in an operational sense to denote a topology-aware organization of textual semantic units induced from token/entity interactions, rather than a strict low-dimensional differentiable manifold.