Quality Controlled Paraphrase Generation
Elron Bandel, Ranit Aharonov, et al.
ACL 2022
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.
Elron Bandel, Ranit Aharonov, et al.
ACL 2022
Chul Sung, Tengfei Ma, et al.
EMNLP-IJCNLP 2019
Sara Rosenthal, Ken Barker, et al.
EMNLP-IJCNLP 2019
Haggai Roitman, Gilad Barkai, et al.
ICDEW 2014