Papers by Xudong Jin

2 papers
GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion (2026.acl-long)

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Challenge: Existing quantization-based approaches to knowledge Graph Completion (KGC) are incomplete.
Approach: They propose a framework that generates semantically coherent discrete codes for KG entities . they introduce a Granular Semantic Enhancement module that injects hierarchical knowledge into the codebook .
Outcome: The proposed framework outperforms existing text-based and embedding-based baselines in the KGC domain.

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