Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphs (2024.emnlp-main)
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| Challenge: | Existing methods to predict instances for missing relations on knowledge graphs are limited by their limited training examples. |
| Approach: | They propose a context-aware adapter for few-shot relation learning in KGs . they propose tunable relation adaptation and contextual information for each relation . |
| Outcome: | Experiments on three benchmark KGs validate the superiority of RelAdapter over state-of-the-art methods. |
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