Papers with minimum neural architecture
FUSE: Measure-Theoretic Compact Fuzzy Set Representation for Taxonomy Expansion (2024.findings-acl)
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| Challenge: | Existing work models taxonomy concepts as vectors or geometric objects, but fuzzy sets are efficient for concept modeling. |
| Approach: | They propose a set representation learning task based on fuzzy set approximation . they demonstrate remarkable improvements in taxonomy expansion using FUSE . |
| Outcome: | The proposed framework improves taxonomy expansion performance by 23% over baselines. |