Papers by Sinian Zhang

1 papers
DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains (2025.findings-emnlp)

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Challenge: Knowledge graph completion (KGC) aims to predict missing triples in knowledge graphs . current approaches encode graph context in textual form, which fails to exploit its potential .
Approach: a new method is proposed to predict missing triples in knowledge graphs by leveraging existing triples and textual information.
Outcome: The proposed model learns structural embeddings and logical rules within the KG and extracts a subgraph for each query guided by the learned rules.

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