{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ltrc-mup-2022-multi-perspective-scientific","title":"LTRC @MuP 2022: Multi-Perspective Scientific Document Summarization Using Pre-trained Generation Models","arxiv_id":null,"date":"2022-10-01","proceeding":"sdp (COLING) 2022 10","authors":["Ashok Urlana","Nirmal Surange","Manish Shrivastava"],"abstract":"The MuP-2022 shared task focuses on multiperspective scientific document summarization. Given a scientific document, with multiple reference summaries, our goal was to develop a model that can produce a generic summary covering as many aspects of the document as covered by all of its reference summaries. This paper describes our best official model, a finetuned BART-large, along with a discussion on the challenges of this task and some of our unofficial models including SOTA generation models. Our submitted model out performedthe given, MuP 2022 shared task, baselines on ROUGE-2, ROUGE-L and average ROUGE F1-scores. Code of our submission can be ac- cessed here.","url_abs":"https://aclanthology.org/2022.sdp-1.35","url_pdf":"https://aclanthology.org/2022.sdp-1.35.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"ltrc-mup-2022-multi-perspective-scientific","repo_url":"https://github.com/ashokurlana/ltrc-mup-coling-2022","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"document-summarization","task_name":"Document Summarization"},{"task_slug":"scientific-article-summarization","task_name":"Scientific Document Summarization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}