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Found 5 papers, 5 papers with code
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding
Most existing negative sampling methods assume that non-existent triples with high scores are high-quality negative triples.
Global Structure Knowledge-Guided Relation Extraction Method for Visually-Rich Document
GOSE initiates by generating preliminary relation predictions on entity pairs extracted from a scanned image of the document.
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting
We study the knowledge extrapolation problem to embed new components (i. e., entities and relations) that come with emerging knowledge graphs (KGs) in the federated setting.
NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs
NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs.
ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning
This paper presents our systems for the three Subtasks of SemEval Task4: Reading Comprehension of Abstract Meaning (ReCAM).
Ranked #1 on
Reading Comprehension
on ReCAM
(using extra training data)
