Document-level RE with incomplete labeling
3 papers with code • 2 benchmarks • 2 datasets
Re-DocRED
Most implemented papers
A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of Labeling
www-ye/ssr-pu
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To solve the common incomplete labeling problem, we propose a unified positive-unlabeled learning framework - shift and squared ranking loss positive-unlabeled (SSR-PU) learning.
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling
www-ye/p3m
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Motivated by this, we propose a positive-augmentation and positive-mixup positive-unlabeled metric learning framework (P3M).
TTM-RE: Memory-Augmented Document-Level Relation Extraction
chufangao/ttm-re
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Document-level relation extraction aims to categorize the association between any two entities within a document.
