TASK DEFINITION: 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.
PROBLEM: Before designing this NLP toolkit, we conducted a survey among engineers and identified a spectrum of three typical personas.

SOLUTION: How do the authors evidence the claim that many engineers find it a big overhead to choose from multiple frameworks, models and optimization techniques?

PROBLEM: For the comparison we chose the best text model for each representation. As expected we obtain the largest improvement ($22-26\%$ E.R) when text-based unsupervised models are combined with image representations.

SOLUTION: How much better is inference that has addition of image representation compared to text-only representations? 

PROBLEM: As shown in Table TABREF12, the T-T model significantly outperforms the LSTM-based RNN-T baseline.

SOLUTION:
What was previous state of the art model?