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.
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Question: We crowdsourced multiple-choice questions in two parts, encouraging workers to be imaginative and varied in their use of language. First, workers were given a seed qualitative relation q+/-( INLINEFORM0 ) in the domain, expressed in English (e.g., “If a surface has more friction, then an object will travel slower”), and asked to enter two objects, people, or situations to compare.

Answer: Do all questions in the dataset allow the answers to pick from 2 options?


Question: The Title-to-Story system is a baseline, which generates directly from topic.

Answer: What are the baselines?


Question: The model has around 836M parameters, of which only 66K are byte embeddings.

Answer:
How many parameters does the model have?