GASP! Generating Abstracts of Scientific Papers from Abstracts of Cited Papers
This addresses the problem of modeling scientific creativity for researchers, but it is incremental as it builds on existing summarization methods.
The paper introduces the novel task of generating scientific paper abstracts from cited paper abstracts (GASP) to study scientific creativity, and experiments with two vanilla summarization systems to analyze its complexity.
Creativity is one of the driving forces of human kind as it allows to break current understanding to envision new ideas, which may revolutionize entire fields of knowledge. Scientific research offers a challenging environment where to learn a model for the creative process. In fact, scientific research is a creative act in the formal settings of the scientific method and this creative act is described in articles. In this paper, we dare to introduce the novel, scientifically and philosophically challenging task of Generating Abstracts of Scientific Papers from abstracts of cited papers (GASP) as a text-to-text task to investigate scientific creativity, To foster research in this novel, challenging task, we prepared a dataset by using services where that solve the problem of copyright and, hence, the dataset is public available with its standard split. Finally, we experimented with two vanilla summarization systems to start the analysis of the complexity of the GASP task.