Neural Multi-task Learning in Automated Assessment
Table 2: Performance of BiLSTM model on public-FCE test set for GED with multi-task training objectives (cumulatively) for entire essay contexts.
['Error Detection Cost', 'Error Detection Precision', 'Error Detection Recall', 'Error Detection  [ITALIC] F0.5']
(+ Eaes) for the GED task. We see a small but insignificant increase in performance (F0.5) when using the AES training objective.