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Identifying beneficial task relations for multi task learning in deep neural networks

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Table 1: Dataset characteristics for the individual tasks as defined in Table 2, as well as single-task modelperformance on test data (micro-averaged F1 ).
Figure 1: Relative gains and losses (in percent)over main task micro-averaged F1when incor-porating auxiliary tasks (columns) compared tosingle-task models for the main tasks (rows).
Table 4: Predictors of MTL benefit by logistic re-gression model coefficient (absolute value).

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