SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers

Understand

Scientific literature is typically dense, requiring significant background knowledge and deep comprehension for effective engagement.

• We introduce SciDQA, a new dataset for reading comprehension that challenges LLMs for a deep understanding of scientific articles, consisting of 2,937 QA pairs.
• Unlike other scientific QA datasets, SciDQA sources questions from peer reviews by domain experts and answers by paper authors, ensuring a thorough examination of the literature.
• We enhance the dataset's quality through a process that carefully filters out lower quality questions, decontextualizes the content, tracks the source document across different versions, and incorporates a bibliography for multi-document question-answering.