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08/15/2023
A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning
Knowledge Graph Embedding (KGE) has proven to be an effective approach t...
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05/22/2023
Lion: Adversarial Distillation of Closed-Source Large Language Model
The practice of transferring knowledge from a sophisticated, closed-sour...
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04/28/2023
NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning
Since the dynamic characteristics of knowledge graphs, many inductive kn...
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04/23/2023
Modality-Aware Negative Sampling for Multi-modal Knowledge Graph Embedding
Negative sampling (NS) is widely used in knowledge graph embedding (KGE)...
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03/03/2023
Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
Knowledge graphs (KG) are essential background knowledge providers in ma...
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02/03/2023
Generalizing to Unseen Elements: A Survey on Knowledge Extrapolation for Knowledge Graphs
Knowledge graphs (KGs) have become effective knowledge resources in dive...
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10/20/2022
Tele-Knowledge Pre-training for Fault Analysis
In this work, we share our experience on tele-knowledge pre-training for...
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10/08/2022
Relational Message Passing for Fully Inductive Knowledge Graph Completion
In knowledge graph completion (KGC), predicting triples involving emergi...
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05/10/2022
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting
We study the knowledge extrapolation problem to embed new components (i....
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02/25/2022
NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs
NeuralKG is an open-source Python-based library for diverse representati...
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10/27/2021
Standing on the Shoulders of Predecessors: Meta-Knowledge Transfer for Knowledge Graphs
Knowledge graphs (KGs) have become widespread, and various knowledge gra...
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10/24/2020
FedE: Embedding Knowledge Graphs in Federated Setting
Knowledge graphs (KGs) consisting of triples are always incomplete, so i...
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04/02/2020
PaStaNet: Toward Human Activity Knowledge Engine
Existing image-based activity understanding methods mainly adopt direct ...
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09/04/2019
Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs
Link prediction is an important way to complete knowledge graphs (KGs), ...
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04/13/2019