Papers by Yang Jinrui

2 papers
Towards Open-Domain Topic Classification (2022.naacl-demo)

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Challenge: Existing supervised classification models are insensitive to class names, but are no longer effective in open-domain tasks where the taxonomy is unbounded.
Approach: They propose a topic classification system that accepts user-defined taxonomy in real time . they train a pretrained language model on a new Wikipedia dataset and train it on Wikipedia .
Outcome: The proposed system improves over existing zero-shot models and performs competitively with weakly-supervised models trained on in-domain data.
RTFE: A Recursive Temporal Fact Embedding Framework for Temporal Knowledge Graph Completion (2021.naacl-main)

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Challenge: Existing methods for static knowledge graph embedding (SKGE) ignore the continuity of states of TKGs in time evolution.
Approach: They propose a Recursive Temporal Fact Embedding framework to transplant SKGE models to TKGs and enhance the performance of existing TKGE models.
Outcome: The proposed framework can be used to transplant SKGE models to TKGs and improve existing models for TKG completion.

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