In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

The ensembles were formed by simply averaging the predictions from the constituent single models.
How does their ensemble method work?

We adopt a DNN-based acoustic model BIBREF0 with 11 hidden layers and the alignment used to train the model is derived from a HMM-GMM model trained with SAT criterion.
What are the deep learning architectures used in the task?

To further demonstrate the effectiveness of the additional task-specific BiRNN layers in our architecture, we conducted an ablation study using the CoNLL04 dataset. We trained and evaluated in the same manner described above, using the same hyperparameters, with the following exceptions:

We used either (i) zero NER-specific BiRNN layers, (ii) zero RE-specific BiRNN layers, or (iii) zero task-specific BiRNN layers of any kind.

We increased the number of shared BiRNN layers to keep the total number of model parameters consistent with the number of parameters in the baseline model.

We average the results for each set of hyperparameter across three trials with random weight initializations.

What were the variables in the ablation study?