Title
Adversarial Learning with Domain-Adaptive Pretraining for Few-Shot Relation Classification across Domains
Abstract
The existing methods for domain-adaptive few-shot relation classification based on word embeddings or pretraining models trained on massive corpora, are not strong enough to cover the wide disparity of text and relation definitions to the specific target domain, leading to the inferior performance. To fill in this gap, here we propose an enhanced adversarial approach utilizing domain-adaptive pret...
Year
DOI
Venue
2021
10.1109/ICCCS52626.2021.9449297
2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)
Keywords
DocType
ISBN
Adaptation models,Communication systems,Conferences,Semantics,Bit error rate,Complexity theory,Task analysis
Conference
978-1-6654-1256-8
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Wen Qian100.34
Zhu Yuesheng211239.21