Papers with SLICE
SLICE: Supersense-based Lightweight Interpretable Contextual Embeddings (2020.coling-main)
Copied to clipboard
| Challenge: | Contextualised embeddings are a key component of human languages but their opaqueness makes it difficult to interpret their behaviour. |
| Approach: | They propose a weakly supervised method to learn interpretable embeddings from raw corpora and seed words. |
| Outcome: | The proposed model can represent both a word and its context as embeddings into the same compact space, whose dimensions correspond to interpretable supersenses. |