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.

[EX Q]: The experimental results are shown in Table 1, where it can be seen that autoencoders outperformed MLP and CNN outperformed autoencoders with the highest achieved accuracy of 82.6%.
Question: What was their performance on the dataset?
[EX A]: accuracy of 82.6%

[EX Q]: We first conduct experiments to compare the performance of FlowSeq with strong baseline models, including NAT w/ Fertility BIBREF6, NAT-IR BIBREF7, NAT-REG BIBREF25, LV NAR BIBREF26, CTC Loss BIBREF27, and CMLM BIBREF8.
Question: What non autoregressive NMT models are used for comparison?
[EX A]: NAT w/ Fertility NAT-IR NAT-REG LV NAR CTC Loss CMLM

[EX Q]: The dataset contains approximately 30M utterances of fictional characters.
Question: How large is the dataset?
[EX A]:
30M utterances