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.

Q: We compared our multi-turn emotionally engaging dialog model (denoted as MEED) with two baselines—the vanilla sequence-to-sequence model (denoted as S2S) and HRAN.

A: What two baseline models are used?
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Q: We evaluate performance of our models on the SQUAD BIBREF16 dataset (denoted $\mathcal {S}$ ). We use the same split as that of BIBREF4 , where a random subset of 70,484 instances from $\mathcal {S}\ $ are used for training ( ${\mathcal {S}}^{tr}$ ), 10,570 instances for validation ( ${\mathcal {S}}^{val}$ ), and 11,877 instances for testing ( ${\mathcal {S}}^{te}$ ).

A: Which datasets are used to train this model?
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Q: Table TABREF20 shows that, on WoZ and DSTC2 datasets, SIM model has the same number of parameters, which is only 23% and 19% of that in GLAD model.

A:
How do they measure model size?
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