  We present a novel system providing summaries for Computer Science
publications. Through a qualitative user study, we identified the most valuable
scenarios for discovery, exploration and understanding of scientific documents.
Based on these findings, we built a system that retrieves and summarizes
scientific documents for a given information need, either in form of a
free-text query or by choosing categorized values such as scientific tasks,
datasets and more. Our system ingested 270,000 papers, and its summarization
module aims to generate concise yet detailed summaries. We validated our
approach with human experts.
