StackOverflowVQA: Stack Overflow Visual Question Answering Dataset
This addresses a gap for researchers and developers in AI-assisted programming by focusing on software-specific visual questions, though it is incremental as it applies existing VQA concepts to a new domain.
The authors tackled the lack of visual question answering datasets for software-related problems by introducing StackOverflowVQA, a dataset from Stack Overflow with images and human-generated answers, and provided a baseline using the GIT model.
In recent years, people have increasingly used AI to help them with their problems by asking questions on different topics. One of these topics can be software-related and programming questions. In this work, we focus on the questions which need the understanding of images in addition to the question itself. We introduce the StackOverflowVQA dataset, which includes questions from StackOverflow that have one or more accompanying images. This is the first VQA dataset that focuses on software-related questions and contains multiple human-generated full-sentence answers. Additionally, we provide a baseline for answering the questions with respect to images in the introduced dataset using the GIT model. All versions of the dataset are available at https://huggingface.co/mirzaei2114.