This article focuses on the task of completing knowledge graphs by predicting linkages between entities, which is fundamental yet critical.
Jan 13, 2022 · This paper focuses on knowledge graph completion by predicting linkage between entities, which is a fundamental yet critical task.
Apr 28, 2022 · This paper focuses on knowledge graph completion by predicting linkage be- tween entities, which is a fundamental yet critical task. Semantic.
Semantic networks, exemplified by the knowledge graph, serve as a means to represent knowledge by lever- aging the structure of a graph.
A novel architecture for knowledge graphs known as LP-BERT, which incorporates a language model and proposes a novel data augmentation approach that ...
To address this challenge, we propose a novel architecture for knowledge graphs known as LP-BERT, which incorporates a language model. LP-BERT consists of two ...
Multi-Task Pre-Training Language Model For Semantic Network Completion. Uploaded by. Dương Vũ Minh. 0 ratings0% found this document useful (0 votes).
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A multi-task learning based pre-trained language model for code understanding and code generation with a Transformer-based neural architecture that adopts ...
We evaluate our approach on four types of language understanding tasks – natural language inference, question answering, semantic similarity, and text ...
We propose a unified multi-task learning framework capable of concurrently handling multiple tasks within a single model, including column named entity ...