Hyper-Align is a hypergraph-native framework that serializes high-order relations into LLM-compatible tokens via HIDT-O templates and a HIP projector, outperforming graph-centric methods on HyperAlign-Bench.
LLM- guided multi-view hypergraph learning for human-centric explainable recommendation.arXiv preprint arXiv:2401.08217, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
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HYVINT introduces an intensity-driven incidence mechanism and tractable variational estimator for hypergraph generation, with error bounds and empirical gains in fidelity, novelty, and diversity.
citing papers explorer
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Hypergraph as Language
Hyper-Align is a hypergraph-native framework that serializes high-order relations into LLM-compatible tokens via HIDT-O templates and a HIP projector, outperforming graph-centric methods on HyperAlign-Bench.
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HYVINT: Intensity-Driven Hypergraph Generation with Variational Representations
HYVINT introduces an intensity-driven incidence mechanism and tractable variational estimator for hypergraph generation, with error bounds and empirical gains in fidelity, novelty, and diversity.