Papers with fine-tuned systems

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.
Background Summarization of Event Timelines (2023.emnlp-main)

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Challenge: Generating concise summaries of news events is a challenging task for newcomers to a news story.
Approach: They propose a task of background news summarization that complements each timeline update with a background summary of relevant preceding events.
Outcome: The proposed system performs well on a question-answering-based evaluation metric, Background Utility Score (BUS).

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