Papers with gated mechanism

2 papers
One-shot Learning for Question-Answering in Gaokao History Challenge (C18-1)

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Challenge: Existing work on deep question-answering tasks from admission exams is challenging since it requires effective representation to capture complicated semantic relations between questions and answers.
Approach: They propose a hybrid neural model for deep question-answering task from history examinations using a gated network and a machine labeler.
Outcome: The proposed model obtains substantial performance gains over baseline models in terms of multiple evaluation metrics.
Implicit Relation Linking for Question Answering over Knowledge Graph (2022.findings-acl)

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Challenge: Existing methods rely on textual similarities between NL and KG to build relation links.
Approach: They propose an implicit relation linking method called ImRL which links relation phrases in NL to relation paths in KG.
Outcome: The proposed method significantly outperforms state-of-the-art methods on two benchmarks and a newly-created datasets.

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