Papers by Ritika Mangla

2 papers
QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing (2023.emnlp-main)

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Challenge: Existing evaluation metrics poorly approximate parser quality, says a new study . questions under discussion is a linguistic framework that views discourse as asking questions and answering them .
Approach: They propose a framework for automatic evaluation of QUD parsing . they use a dataset of fine-grained evaluation of 2,190 QUD questions .
Outcome: The proposed framework shows that satisfying constraints of QUD is still challenging for modern LLMs.
Which questions should I answer? Salience Prediction of Inquisitive Questions (2024.emnlp-main)

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Challenge: Recent work in NLP has taken advantage of question generation capabilities of LLMs to enhance a wide range of applications.
Approach: They propose a salience predictor for inquisitive questions that is instruction-tuned . they show that highly salient questions are empirically more likely to be answered in the same article .
Outcome: The proposed model is based on linguist-annotated salience scores of 1,766 questions . it shows that answering salient questions improves comprehension of the text .

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