Papers with DocNLI

2 papers
DocNLI: A Large-scale Dataset for Document-level Natural Language Inference (2021.findings-acl)

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Challenge: Existing studies focus on sentence-level inference, which limits its application in downstream NLP problems.
Approach: They propose to construct a large-scale dataset for document-level NLI that can be used to study NLP problems.
Outcome: The proposed model performs well on popular sentence-level benchmarks and generalizes well to out-of-domain NLP tasks that rely on inference at document granularity.
Consecutive Question Generation via Dynamic Multitask Learning (2022.findings-emnlp)

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Challenge: , . ; ) ()((); ()) .())((2): ""().
Approach: They propose a sequential sequential question-answer generation task with auxiliary tasks generating other elements to generate logically related question-anchor pairs to understand a passage.
Outcome: The proposed framework improves question generation significantly and benefit multiple related tasks.

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