mup

# MuP - Multi Perspective Scientific Document Summarization

Generating summaries of scientific documents is known to be a challenging task. Majority of existing work in summarization assumes only one single best gold summary for each given document. Having only one gold summary negatively impacts our ability to evaluate the quality of summarization systems as writing summaries is a subjective activity. At the same time, annotating multiple gold summaries for scientific documents can be extremely expensive as it requires domain experts to read and understand long scientific documents. This shared task will enable exploring methods for generating multi-perspective summaries. We introduce a novel summarization corpus, leveraging data from scientific peer reviews to capture diverse perspectives from the reader's point of view.

# MuP：多视角科学文献摘要生成（Multi Perspective Scientific Document Summarization）
科学文献摘要生成是一项公认的极具挑战性的任务。现有摘要生成领域的绝大多数研究均默认，每份待处理科学文献仅存在唯一最优的金标准参考摘要（gold summary）。由于摘要撰写本质上属于主观创作行为，仅依赖单条金标准参考摘要会严重制约摘要生成系统的质量评估效果。与此同时，为科学文献标注多条金标准参考摘要的成本极高，因为该流程需要领域专家阅读并理解篇幅冗长的科学文献。本次共享任务旨在探索多视角摘要生成的相关技术路径。我们构建了一款全新的摘要生成语料库，该语料库依托科学文献的同行评审数据，从读者视角出发捕捉多样化的摘要生成视角。