Papers by Nandan Sarkar

1 papers
SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers (2024.emnlp-main)

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Challenge: SciDQA is a dataset for question-answering that challenges language models to deeply understand scientific articles.
Approach: They propose a new dataset for reading comprehension that challenges language models to deeply understand scientific articles consisting of 2,937 QA pairs.
Outcome: The SciDQA dataset is based on 2,937 QA pairs and decontextualizes the content, tracks the source document across different versions, and incorporates a bibliography for multi-document question-answering.

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