Long-Distance Dependencies Don’t Have to Be Long: Simplifying through Provably (Approximately) Optimal Permutations (P19-2)
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| Challenge: | Neural models at the sentence level often need to model the interaction between words . however, there is no guarantee that the standard ordering of words is computationally efficient or optimal . |
| Approach: | They propose to use a dependency parse as a proxy for inter-word dependencies in a sentence to simplify the sentence with combinatorial objectives imposed on the sentence-parse pair. |
| Outcome: | The proposed model improves classification accuracy and reduces classification error by 2.0% over the previous state of the art. |
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More Embeddings, Better Sequence Labelers? (2020.findings-emnlp)
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