Papers by Zhanpeng Guan
Should We Use a Fixed Embedding Size? Customized Dimension Sizes for Knowledge Graph Embedding (2025.coling-main)
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| Challenge: | Knowledge Graph Embedding (KGE) aims to project entities and relations into a low-dimensional space, which is crucial for knowledge completion, fusion, and inference. |
| Approach: | They propose to embed entities and relations into a low-dimensional space to enable knowledge Graphs to be effectively used by downstream AI tasks. |
| Outcome: | The proposed framework is universal and flexible, suitable for various KGE models. |