Papers with Distributional Semantic Models
A Tale of Two Laws of Semantic Change: Predicting Synonym Changes with Distributional Semantic Models (2023.starsem-1)
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| Challenge: | Lexical Semantic Change is the study of how the meaning of words evolves through time. |
| Approach: | They propose to use distributional models to detect whether LD or LPC operate for given word pairs. |
| Outcome: | The proposed frameworks achieve a balanced accuracy above 0.6 on the dataset. |
Cross-Topic Distributional Semantic Representations Via Unsupervised Mappings (N19-1)
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| Challenge: | Existing distributional semantic models cannot capture the distinct meanings of polysemous words, resulting in conflated word representations of diverse contextual semantics. |
| Approach: | They propose a distributional semantic model that learns multiple representations of a word based on different topics. |
| Outcome: | The proposed model outperforms single-prototype models on NLP downstream tasks. |