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:
Task 1: Quora Duplicate Question Pair Detection Task 2: Ranking questions in Bing's People Also Ask

Ex Output:
On which tasks do they test their conflict method?


Ex Input:
Our conversational agent uses two architectures to simulate a specialized reminiscence therapist. The block in charge of generating questions is based on the work Show, Attend and Tell BIBREF13. This work generates descriptions from pictures, also known as image captioning.

Ex Output:
Is machine learning system underneath similar to image caption ML systems?


Ex Input:
In particular, we perform an extensive set of experiments on standard benchmarks for bilingual dictionary induction and monolingual and cross-lingual word similarity, as well as on an extrinsic task: cross-lingual hypernym discovery. For both the monolingual and cross-lingual settings, we can notice that our models generally outperform the corresponding baselines.  As can be seen in Table 1 , our refinement method consistently improves over the baselines (i.e., VecMap and MUSE) on all language pairs and metrics. First and foremost, in terms of model-wise comparisons, we observe that our proposed alterations of both VecMap and MUSE improve their quality in a consistent manner, across most metrics and data configurations.

Ex Output:

What are the tasks that this method has shown improvements?