TASK DEFINITION: In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.
PROBLEM: In addition, we have another independent human evaluation task about the style strength – we present the generated headlines from TitleStylist and baselines to the human judges and let them choose the one that most conforms to the target style such as humor. Then we define the style strength score as the proportion of choices. 
 Question: How is presence of three target styles detected?

SOLUTION: human evaluation task about the style strength

PROBLEM: We consider QA PGNet and Multi-decoder QA PGNet with lookup table embedding as baseline models and improve on the baselines with other variations described below. 
 Question: What is the baseline?

SOLUTION: QA PGNet Multi-decoder QA PGNet with lookup table embedding

PROBLEM: To study how the multimodal context can boost the performance compared to an unimodal context we evaluate different models: a Feature Concatenation Model (FCM), a Spatial Concatenation Model (SCM) and a Textual Kernels Model (TKM). 
 Question: What different models for multimodal detection were proposed?

SOLUTION:
Feature Concatenation Model (FCM) Spatial Concatenation Model (SCM) Textual Kernels Model (TKM)