Embedding Dimension Importance (EDI) ranks embedding dimensions by how strongly they encode individual linguistic properties, and a handful of top-ranked dimensions can recover most of a full classifier's accuracy.
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Disentangling Linguistic Features with Dimension-Wise Analysis of Vector Embeddings
Embedding Dimension Importance (EDI) ranks embedding dimensions by how strongly they encode individual linguistic properties, and a handful of top-ranked dimensions can recover most of a full classifier's accuracy.