Unifying Large Language Models and Knowledge Graphs: A Roadmap

Author:

Pan Shirui1ORCID,Luo Linhao2ORCID,Wang Yufei2,Chen Chen3ORCID,Wang Jiapu4ORCID,Wu Xindong5ORCID

Affiliation:

1. School of Information and Communication Technology and Institute for Integrated and Intelligent Systems (IIIS), Griffith University, Nathan, QLD, Australia

2. Department of Data Science and AI, Monash University, Melbourne, VIC, Australia

3. Nanyang Technological University, Singapore

4. Faculty of Information Technology, Beijing University of Technology, Beijing, China

5. Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, Hefei, China

Funder

Australian Research Council

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference201 articles.

1. BERT: Pre-training of deep bidirectional transformers for language understanding;Devlin,2018

2. RoBERTa: A robustly optimized bert pretraining approach;Liu,2019

3. Exploring the limits of transfer learning with a unified text-to-text transformer;Raffel;J. Mach. Learn. Res.,2020

4. Generalizing Question Answering System with Pre-trained Language Model Fine-tuning

5. BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

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