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.

Ex Input:
We use GraphParser without paraphrases as our baseline. This gives an idea about the impact of using paraphrases We compare our paraphrasing models with monolingual machine translation based model for paraphrase generation BIBREF24 , BIBREF36 . In particular, we use Moses BIBREF37 to train a monolingual phrase-based MT system on the Paralex corpus. Finally, we use Moses decoder to generate 10-best distinct paraphrases for the test questions.

Ex Output:
What are the baselines?


Ex Input:
The proposed Multimodal Differential Network (MDN) consists of a representation module and a joint mixture module. We use a triplet network BIBREF41 , BIBREF42 in our representation module. The triplet network consists of three sub-parts: target, supporting, and contrasting networks. All three networks share the same parameters. The Mixture module brings the image and caption embeddings to a joint feature embedding space.

Ex Output:
How do the authors define a differential network?


Ex Input:
We apply Han to such conversations in a sequential manner by feeding each user turn to Han as they occur, to determine if the conversation should escalate. If so, the user will be transferred to a live chat representative to continue the conversation. The user must wait for the human representative to review the IVA chat history and resume the failed task.

Ex Output:

How do they gather human reviews?