Papers by Keshav Balasubramanian
StATIK: Structure and Text for Inductive Knowledge Graph Completion (2022.findings-naacl)
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Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, Greg Ver Steeg
| Challenge: | Knowledge graphs (KGs) represent incomplete knowledge bases. |
| Approach: | They propose to use language models to extract semantic information from text descriptions while using Message Passing Neural Networks to capture structural information. |
| Outcome: | The proposed model achieves state of the art on three challenging inductive baselines. |