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Metric Learning for Dynamic Text Classification

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Figure

Figure 1: Examples of dynamic classification. In thehierarchical setting (left), new labels are created bysplitting and merging old labels.In the flat setting(right), arbitrary labels can be added or removed.
Table 1: Test accuracy for each dataset and method. Columns indicate the number of examples per label nfineused in the fine tuning stage
Table 2: Test accuracy for each dataset and method.Columns indicate the number of examples per labelused for fine-tuning and/or creating prototype vectors.

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