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@@ -207,12 +207,12 @@ The high-level captions capture the human interpretation of the scene, providing
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  From the paper:
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- >**Pilot** We run a pilot study with the double goal of collecting feedback and defining the task instructions.
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  >With the results from the pilot we design a beta version of the task and we run a small batch of cases on the crowd-sourcing platform.
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  >We manually inspect the results and we further refine the instructions and the formulation of the task before finally proceeding with the
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  >annotation in bulk. The final annotation form is shown in Appendix D.
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- >***Procedure*** The participants are shown an image and three questions regarding three aspects or axes: _scene_, _actions_ and _rationales_
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  > i,e. _Where is the picture taken?_, _What is the subject doing?_, _Why is the subject doing it?_. We explicitly ask the participants to use
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  >their personal interpretation of the scene and add examples and suggestions in the instructions to further guide the annotators. Moreover,
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  >differently from other VQA datasets like (Antol et al., 2015) and (Zhu et al., 2016), where each question can refer to different entities
 
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  From the paper:
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+ >**Pilot:** We run a pilot study with the double goal of collecting feedback and defining the task instructions.
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  >With the results from the pilot we design a beta version of the task and we run a small batch of cases on the crowd-sourcing platform.
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  >We manually inspect the results and we further refine the instructions and the formulation of the task before finally proceeding with the
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  >annotation in bulk. The final annotation form is shown in Appendix D.
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+ >***Procedure:*** The participants are shown an image and three questions regarding three aspects or axes: _scene_, _actions_ and _rationales_
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  > i,e. _Where is the picture taken?_, _What is the subject doing?_, _Why is the subject doing it?_. We explicitly ask the participants to use
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  >their personal interpretation of the scene and add examples and suggestions in the instructions to further guide the annotators. Moreover,
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  >differently from other VQA datasets like (Antol et al., 2015) and (Zhu et al., 2016), where each question can refer to different entities