In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Input: Consider Input: Furthermore, the basic seq2seq assumes a strict order between generated tokens, but in reality, we should not severely punish the model when it predicts the correct tokens in the wrong order.
Question: Do they impose any grammatical constraints over the generated output?

Output: No

Input: Consider Input: SIGHAN Bakeoff defines two types of evaluation settings, closed test limits all the data for learning should not be beyond the given training set, while open test does not take this limitation BIBREF21.
Question: What is meant by closed test setting?

Output: closed test limits all the data for learning should not be beyond the given training set, while open test does not take this limitation

Input: Consider Input: An attention-based sequence-to-sequence model with the emoji vector as additional input as discribed in MojiTalk BIBREF16. CVAE.
An RNN-based conditional variational autoencoder for dialogue response generation BIBREF16, which uses a multivariate Gaussian latent variable to model the response and concatenate it with the last hidden state of the encoder as the initial state of the decoder. KL annealing, early stopping strategy and bag-of-word auxiliary loss are applied during the training. We use the implementation released by BIBREF16
Question: What baselines other than standard transformers are used in experiments?
Output: attention-based sequence-to-sequence model CVAE