Papers with WiC benchmarks
A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection (2024.findings-acl)
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| Challenge: | Existing Word-in-Context (WiC) datasets are used to detect temporal semantic changes of words. |
| Approach: | They propose a supervised two-staged SCD method that uses existing Word-in-Context (WiC) datasets to predict temporal semantic changes of words. |
| Outcome: | The proposed method achieves strong performance in multiple languages and significant improvements on WiC benchmarks. |