Senci Ying


2021

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LongSumm 2021: Session based automatic summarization model for scientific document
Senci Ying | Zheng Yan Zhao | Wuhe Zou
Proceedings of the Second Workshop on Scholarly Document Processing

Most summarization task focuses on generating relatively short summaries. Such a length constraint might not be appropriate when summarizing scientific work. The LongSumm task needs participants generate long summary for scientific document. This task usual can be solved by language model. But an important problem is that model like BERT is limit to memory, and can not deal with a long input like a document. Also generate a long output is hard. In this paper, we propose a session based automatic summarization model(SBAS) which using a session and ensemble mechanism to generate long summary. And our model achieves the best performance in the LongSumm task.
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