K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain

K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain

The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks. But two significant constraints, the available training data size and the understanding of domain-specific context, hamper the pre-trained langu...

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Bibliographic Details
Main Authors: Vivek Kumar, Diego Reforgiato Recupero, Rim Helaoui, Daniele Riboni
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep learning
machine learning
knowledge graphs
knowledge graphs embeddings
GPT-2
BERT
Online Access:https://ieeexplore.ieee.org/document/9866735/
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