Structured (De)composable Representations Trained with Neural Networks
Table 1: F1 scores, precision (PREC) and recall (REC) for different models for the multi-label classification task. σ is the standard deviation of the F1 score over three runs. All results are the average of three runs.
['[BOLD] MODEL', '[BOLD] METHOD', '[ITALIC] ne', '[ITALIC] nl', '[ITALIC] R', '[BOLD] F1', '[BOLD] PREC', '[BOLD] REC', '[ITALIC] σ']
When adding more detailed contextual information in the environments, as is the case for CoDiR (capt), our model outperforms the baseline in all cases.