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Compressibility of Distributed Document Representations
Contemporary natural language processing (NLP) revolves around learning from latent document representations, generated either implicitly by neural language models or explicitly by methods such as doc2vec or similar.
Feature Importance Estimation with Self-Attention Networks
Black-box neural network models are widely used in industry and science, yet are hard to understand and interpret.
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